diff options
Diffstat (limited to 'help')
51 files changed, 1712 insertions, 700 deletions
diff --git a/help/en_US/arburg.xml b/help/en_US/arburg.xml index 6aa017e..775d9c1 100644 --- a/help/en_US/arburg.xml +++ b/help/en_US/arburg.xml @@ -40,34 +40,32 @@ <listitem><para> positive integer value < length(x) - 2</para></listitem></varlistentry> <varlistentry><term>criterion:</term> <listitem><para> string value, takes in "AKICc", "KIC", "AICc", "AIC" and "FPE", default it not using a model-selection criterion</para></listitem></varlistentry> - <varlistentry><term>a, v, k:</term> - <listitem><para> Output variables</para></listitem></varlistentry> + <varlistentry><term>a:</term> + <listitem><para> list of autoregression coefficients.</para></listitem></varlistentry> + <varlistentry><term>v:</term> + <listitem><para> mean square of residual noise from the whitening operation of the Burg lattice filter</para></listitem></varlistentry> + <varlistentry><term>k:</term> + <listitem><para> reflection coefficients defining the lattice-filter embodiment of the model</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. - </para> - <para> This function calculates coefficients of an autoregressive (AR) model of complex data x using the whitening lattice-filter method of Burg. </para> <para> The first argument is the data sampled. The second argument is the number of poles in the model (or limit in case a criterion is supplied). The third parameter takes in the criterion to limit the number of poles. The acceptable values are "AIC", "AKICc", "KIC", "AICc" which are based on information theory. -Output variable a is a list of P+1 autoregression coefficients. -Output variable v is the mean square of residual noise from the whitening operation of the Burg lattice filter. -Output variable k corresponds to the reflection coefficients defining the lattice-filter embodiment of the model. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -arburg([1,2,3,4,5],2) -ans = -1.00000 -1.86391 0.95710 +x = [1,2,3,4,5] ; +poles = 2 ; +arburg(x,poles) ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/arch_rnd.xml b/help/en_US/arch_rnd.xml index 4692e05..fe24c5c 100644 --- a/help/en_US/arch_rnd.xml +++ b/help/en_US/arch_rnd.xml @@ -43,16 +43,25 @@ <refsection> <title>Description</title> <para> -This is an Octave function. It Simulates an ARCH sequence of length t with AR coefficients b and CH coefficients a. The result y(t) follows the model </para> <para> -y(t) = b(1) + b(2) * y(t-1) + … + b(lb) * y(t-lb+1) + e(t), + <latex> + \begin{eqnarray} +y(t) = b(1) + b(2) * y(t-1) + … + b(lb) * y(t-lb+1) + e(t) + \end{eqnarray} + </latex> +<para> where e(t), given y up to time t-1, is N(0, h(t)), with +</para> </para> <para> + <latex> + \begin{eqnarray} h(t) = a(1) + a(2) * e(t-1)^2 + … + a(la) * e(t-la+1)^2 + \end{eqnarray} + </latex> </para> </refsection> @@ -61,14 +70,9 @@ h(t) = a(1) + a(2) * e(t-1)^2 + … + a(la) * e(t-la+1)^2 <programlisting role="example"><![CDATA[ a = [1 2 3 4 5]; b = [7 8 9 10]; +t = 5 ; arch_rnd (a, b, t) -ans = -6.1037e+00 -5.7294e+01 -5.7390e+02 -6.3063e+03 -6.8695e+04 ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/arma_rnd.xml b/help/en_US/arma_rnd.xml index fdf1c26..922bfb3 100644 --- a/help/en_US/arma_rnd.xml +++ b/help/en_US/arma_rnd.xml @@ -48,12 +48,16 @@ <refsection> <title>Description</title> <para> -This is an Octave function. The ARMA model is defined by </para> <para> -x(n) = a(1) * x(n-1) + … + a(k) * x(n-k) -+ e(n) + b(1) * e(n-1) + … + b(l) * e(n-l) + <latex> + \begin{eqnarray} +x(n) = a(1) * x(n-1) + … + a(k) * x(n-k) + e(n) + b(1) * e(n-1) + … + b(l) * e(n-l) + \end{eqnarray} + </latex> +</para> +<para> in which k is the length of vector a, l is the length of vector b and e is Gaussian white noise with variance v. The function returns a vector of length t. </para> <para> @@ -70,13 +74,7 @@ v = 10; t = 5; n = 100; arma_rnd (a, b, v, t, n) -ans = --1.6176e+05 --4.1663e+05 --1.0732e+06 --2.7648e+06 --7.1221e+06 ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/aryule.xml b/help/en_US/aryule.xml index 7d706fd..6ad7b46 100644 --- a/help/en_US/aryule.xml +++ b/help/en_US/aryule.xml @@ -37,29 +37,29 @@ <listitem><para> vector of real or complex numbers, length > 2</para></listitem></varlistentry> <varlistentry><term>p:</term> <listitem><para> positive integer value < length(x) - 1</para></listitem></varlistentry> - <varlistentry><term>a, v, k:</term> - <listitem><para> Output variables</para></listitem></varlistentry> + <varlistentry><term>a:</term> + <listitem><para> gives the AR coefficients </para></listitem></varlistentry> + <varlistentry><term>v:</term> + <listitem><para> gives the variance of the white noise, </para></listitem></varlistentry> + <varlistentry><term>k:</term> + <listitem><para> gives the reflection coefficients to be used in the lattice filter</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. - </para> - <para> This function fits an AR (p)-model with Yule-Walker estimates. The first argument is the data vector which is to be estimated. -Output variable a gives the AR coefficients, v gives the variance of the white noise and k gives the reflection coefficients to be used in the lattice filter. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -aryule([1,2,3,4,5],2) -ans = -1. - 0.8140351 0.1192982 +x = [1,2,3,4,5] ; +poles = 2 ; +arburg(x,poles) ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/autoreg_matrix.xml b/help/en_US/autoreg_matrix.xml index 61fefef..217a151 100644 --- a/help/en_US/autoreg_matrix.xml +++ b/help/en_US/autoreg_matrix.xml @@ -54,11 +54,11 @@ The resulting matrix may be used as a regressor matrix in autoregressions. <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -autoreg_matrix([1,2,3],2) -ans = -1. 0. 0. -1. 1. 0. -1. 2. 1. + +Y = [1,2,3] ; +K = 2 ; +autoreg_matrix(Y,K) + ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/besselap.xml b/help/en_US/besselap.xml index f3236d7..1704b68 100644 --- a/help/en_US/besselap.xml +++ b/help/en_US/besselap.xml @@ -17,7 +17,7 @@ <refnamediv> <refname>besselap</refname> - <refpurpose>Return bessel analog filter prototype.</refpurpose> + <refpurpose>Bessel analog filter prototype.</refpurpose> </refnamediv> @@ -25,7 +25,6 @@ <title>Calling Sequence</title> <synopsis> [zero, pole, gain] = besselap (n) - [zero, pole] = besselap (n) zero = besselap (n) </synopsis> </refsynopsisdiv> @@ -36,36 +35,34 @@ <varlistentry><term>n:</term> <listitem><para> Filter Order</para></listitem></varlistentry> <varlistentry><term>zero:</term> - <listitem><para> Zeros</para></listitem></varlistentry> + <listitem><para> Zeros of filter</para></listitem></varlistentry> <varlistentry><term>pole:</term> - <listitem><para> Poles</para></listitem></varlistentry> + <listitem><para> Poles of filter</para></listitem></varlistentry> <varlistentry><term>gain:</term> - <listitem><para> Gain</para></listitem></varlistentry> + <listitem><para> Gain of filter</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -It Return bessel analog filter prototype of nth order. +It Return Bessel analog filter prototype of nth order. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[zero, pole, gain] = besselap (5) -zero = [](0x0) -pole = - --0.59058 + 0.90721i --0.59058 - 0.90721i --0.92644 + 0.00000i --0.85155 + 0.44272i --0.85155 - 0.44272i - -gain = 1 +n = 5; +[zero, pole, gain] = besselap (n) ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/besself.xml b/help/en_US/besself.xml index b792eaf..f7456d9 100644 --- a/help/en_US/besself.xml +++ b/help/en_US/besself.xml @@ -17,18 +17,19 @@ <refnamediv> <refname>besself</refname> - <refpurpose>This function generates a Bessel filter.</refpurpose> + <refpurpose>Bessel filter design.</refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [a, b] = besself(n, w) - [a, b] = besself (n, w, "high") - [a, b, c] = besself (…) - [a, b, c, d] = besself (…) - […] = besself (…, "z") +[b, a] = besself(n, Wc) +[b, a] = besself (n, Wc, "high") +[b, a] = besself (n, [Wl, Wh]) +[b, a] = besself (n, [Wl, Wh], "stop") +[z, p, g] = besself (…) +[…] = besself (…, "z") </synopsis> </refsynopsisdiv> @@ -36,31 +37,30 @@ <title>Parameters</title> <variablelist> <varlistentry><term>n:</term> - <listitem><para> positive integer value</para></listitem></varlistentry> - <varlistentry><term>w:</term> - <listitem><para> positive real value</para></listitem></varlistentry> + <listitem><para> positive integer value (order of filter)</para></listitem></varlistentry> + <varlistentry><term>W:</term> + <listitem><para> positive real value</para><para> 1).Analog 3dB cutoff frequency/frequencies for analog filter, in the range [0, Inf] {rad/sec}</para><para> 2).Normalised digital 3dB cutoff frequency/frequencies for digital filter, in the range [0, 1] {dimensionless}</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function generates a Bessel filter. The default is a Laplace space (s) filter. -The third parameter takes in high or low, the default value being low. The cutoff is pi*Wc radians. -[z,p,g] = besself(...) returns filter as zero-pole-gain rather than coefficients of the numerator and denominator polynomials. -[...] = besself(...,’z’) returns a discrete space (Z) filter. w must be less than 1. -[a,b,c,d] = besself(...) returns state-space matrices. +This function generates a Bessel filter. The default is a Laplace space (s) or analog filter.</para> +<para>If second argument is scalar the third parameter takes in high or low, the default value being low. The cutoff is Wc rad/sec.</para> +<para>If second argument is vector of length 2 ie [Wl Wh] then third parameter may be pass or stop default is pass for bandpass and band reject filter respectively</para> +<para>[z,p,g] = besself(...) returns filter as zero-pole-gain rather than coefficients of the numerator and denominator polynomials.</para> +<para>[...] = besself(...,’z’) returns a discrete space (Z) filter. Wc must be less than 1 {dimensionless}. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[a,b]=besself(2,3,"low") -a = 9.0000 -b = -1.0000 5.1962 9.0000 +n = 2; +wc = 0.3; +[b, a]=besself(n, wc, "high", "z") + ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/bilinear.xml b/help/en_US/bilinear.xml index 0361759..e6a2e46 100644 --- a/help/en_US/bilinear.xml +++ b/help/en_US/bilinear.xml @@ -17,36 +17,82 @@ <refnamediv> <refname>bilinear</refname> - <refpurpose>Transform a s-plane filter specification into a z-plane specification</refpurpose> + <refpurpose>Transforms a s-plane filter (Analog) into a z-plane filter (Digital) using Bilinear transformation</refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [ZB, ZA] = bilinear (SB, SA, T) - [ZB, ZA] = bilinear (SZ, SP, SG, T) - [ZZ, ZP, ZG] = bilinear (...) + [Zb, Za] = bilinear(Sb, Sa, T) + [Zb, Zb] = bilinear(Sz, Sp, Sg, T) + [Zz, Zp, Zg] = bilinear(...) </synopsis> </refsynopsisdiv> <refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>Sb:</term> + <listitem><para> Numerator coefficient vector in s-domain. </para></listitem></varlistentry> + <varlistentry><term>Sa:</term> + <listitem><para> Denumerator coefficient vector s-domain.</para></listitem></varlistentry> + <varlistentry><term>Sz:</term> + <listitem><para> zeros in s-plane.</para></listitem></varlistentry> + <varlistentry><term>Sp:</term> + <listitem><para> poles in s-plane.</para></listitem></varlistentry> + <varlistentry><term>Sg:</term> + <listitem><para> gain in s-domain.</para></listitem></varlistentry> + <varlistentry><term>T:</term> + <listitem><para> Sampling period (double).</para></listitem></varlistentry> + <varlistentry><term>Zb:</term> + <listitem><para> Numerator coefficient vector in z-domain.</para></listitem></varlistentry> + <varlistentry><term>Za:</term> + <listitem><para> Denumerator coefficient vector z-domain.</para></listitem></varlistentry> + <varlistentry><term>Zz:</term> + <listitem><para> zeros in z-plane.</para></listitem></varlistentry> + <varlistentry><term>Zp:</term> + <listitem><para> poles in z-plane.</para></listitem></varlistentry> + <varlistentry><term>Zg:</term> + <listitem><para> gain in z-domain.</para></listitem></varlistentry> + </variablelist> +</refsection> + +<refsection> <title>Description</title> <para> -Transform a s-plane filter specification into a z-plane specification. Filters can be specified in either zero-pole-gain or transfer function form. The input form does not have to match the output form. 1/T is the sampling frequency represented in the z plane. +a filter design can be transformed from the s-plane to the z-plane while maintaining the band edges by means of the bilinear transform. This maps the left hand side of the s-plane into the interior of the unit circle in z-plane. The mapping is highly non-linear, so you must design your filter with band edges in the s-plane positioned at 2/T tan(w*T/2) so that they will be positioned at w after the bilinear transform is complete. </para> <para> -Note: this differs from the bilinear function in the signal processing toolbox, which uses 1/T rather than T. +It does following transformation from s-plane to z-plane </para> + <para> -Theory: Given a piecewise flat filter design, you can transform it from the s-plane to the z-plane while maintaining the band edges by means of the bilinear transform. This maps the left hand side of the s-plane into the interior of the unit circle. The mapping is highly non-linear, so you must design your filter with band edges in the s-plane positioned at 2/T tan(w*T/2) so that they will be positioned at w after the bilinear transform is complete. -</para> + <latex> + \begin{eqnarray} + s --> \frac{2} {T} \frac {z - 1} {z + 1} + \end{eqnarray} + </latex> + </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[ZB,ZA]=bilinear([1],[2,3],3) +Sz = [1 2 3] +Sp = [4 5 6] +Sg = 1; +T = 1; +[Zb,Za] = bilinear (Sz, Sp, Sg, T) + ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/bitrevorder.xml b/help/en_US/bitrevorder.xml index 996ed26..35ca8f4 100644 --- a/help/en_US/bitrevorder.xml +++ b/help/en_US/bitrevorder.xml @@ -17,15 +17,18 @@ <refnamediv> <refname>bitrevorder</refname> - <refpurpose></refpurpose> + <refpurpose> Returns input data in bit-reversed order </refpurpose> + <para> </para> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [y,i]=bitrevorder(x) + [y,i] = bitrevorder(x) + y = bitrevorder(x) </synopsis> + <para> </para> </refsynopsisdiv> <refsection> @@ -33,13 +36,17 @@ <variablelist> <varlistentry><term>x:</term> <listitem><para> Vector of real or complex values</para></listitem></varlistentry> + <varlistentry><term>y:</term> + <listitem><para> input vector in bit reverse order</para></listitem></varlistentry> + <varlistentry><term>i:</term> + <listitem><para> indices after bit reversing </para></listitem></varlistentry> + <para> </para> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. This function returns the input data after reversing the bits of the indices and reordering the elements of the input array. </para> </refsection> @@ -47,11 +54,8 @@ This function returns the input data after reversing the bits of the indices and <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -1. [y]=bitrevorder ([i,1,3,6i]) -y = [0 + 1i 3 + 0i 1 + 0i 0 + 6i] -2. [y,i]=bitrevorder (['a','b','c','d']) -y = acbd -i = [1 3 2 4] +x = [%i,1,3,6*%i] ; +[y i]=bitrevorder(x) ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/buttap.xml b/help/en_US/buttap.xml index d891af5..9a7a948 100644 --- a/help/en_US/buttap.xml +++ b/help/en_US/buttap.xml @@ -17,15 +17,13 @@ <refnamediv> <refname>buttap</refname> - <refpurpose>Design a lowpass analog Butterworth filter.</refpurpose> + <refpurpose>Produces a lowpass analog prototype Butterworth filter.</refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - z = buttap (n) - [z, p] = buttap (n) [z, p, g] = buttap (n) </synopsis> </refsynopsisdiv> @@ -47,21 +45,23 @@ <refsection> <title>Description</title> <para> -This is an Octave function. -It designs a lowpass analog Butterworth filter of nth order. +It gives a lowpass analog prototype Butterworth filter of nth order. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[z, p, g] = buttap (5) -z = [](0x0) -p = - --0.30902 + 0.95106i -0.80902 + 0.58779i -1.00000 + 0.00000i -0.80902 - 0.58779i -0.30902 - 0.95106i - -g = 1 +n = 5 ; +[z, p, g] = buttap (n) ]]></programlisting> </refsection> + + <refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> + </refsection> + </refentry> diff --git a/help/en_US/butter.xml b/help/en_US/butter.xml index bacacaf..8137c23 100644 --- a/help/en_US/butter.xml +++ b/help/en_US/butter.xml @@ -17,20 +17,19 @@ <refnamediv> <refname>butter</refname> - <refpurpose>This function generates a Butterworth filter.</refpurpose> + <refpurpose>Butterworth filter design..</refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [a, b] = butter (n, w) - [a, b] = butter (n, w, "high") - [a, b] = butter (n, [wl, wh]) - [b, a] = butter (n, [wl, wh], "stop") - [a, b, c] = butter (…) - [a, b, c, d] = butter (…) - […] = butter (…, "s") + [b, a] = butter (n, wc) + [b, a] = butter (n, wc, "high") + [b, a] = butter (n, [wl, wh]) + [b, a] = butter (n, [wl, wh], "stop") + [z, p, g] = butter (…) + […] = butter (…, "s") </synopsis> </refsynopsisdiv> @@ -38,34 +37,39 @@ <title>Parameters</title> <variablelist> <varlistentry><term>n:</term> - <listitem><para> positive integer value</para></listitem></varlistentry> - <varlistentry><term>w:</term> - <listitem><para> positive real value, w in the range [0,1]</para></listitem></varlistentry> + <listitem><para> positive integer value (order of filter).</para></listitem></varlistentry> + <varlistentry><term>wc:</term> + <listitem><para> positive real value,</para><para> 1).Normalised digital 3dB cutoff frequency/frequencies for digital filter, in the range [0, 1] {dimensionless}</para><para> 2).Analog 3dB cutoff frequency/frequencies for analog filter, in the range [0, Inf] {rad/sec}</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function generates a Butterworth filter. Default is a discrete space (Z) filter. -The third parameter takes in low or high, default value is low. The cutoff is pi*Wc radians. -[b,a] = butter(n, [Wl, Wh]) indicates a band pass filter with edges pi*Wl and pi*Wh radians. -[b,a] = butter(n, [Wl, Wh], ’stop’) indicates a band reject filter with edges pi*Wl and pi*Wh radians. -[z,p,g] = butter(...) returns filter as zero-pole-gain rather than coefficients of the numerator and denominator polynomials. -[...] = butter(...,’s’) returns a Laplace space filter, w can be larger than 1. -[a,b,c,d] = butter(...) returns state-space matrices. +This function generates a Butterworth filter. Default is a discrete space (z) or digital filter using Bilinear transformation from s to z plane.</para> + <para>If second argument is scalar the third parameter takes in low or high, default value is low. The cutoff is pi*wc radians.</para> + <para>[b,a] = butter(n, [wl, wh]) indicates a band pass filter with cutoffs pi*Wl and pi*wh radians. </para> + <para>[b,a] = butter(n, [wl, wh], ’stop’) indicates a band reject filter with cutoffs pi*wl and pi*wh radians.</para> + <para>[z,p,g] = butter(...) returns filter as zero-pole-gain rather than coefficients of the numerator and denominator polynomials.</para> + <para>[...] = butter(...,’s’) returns a Laplace space filter,here cutoff(s) wc can be larger than 1 (rad/sec). </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[a,b]=butter(3, 0.7) -a = -0.37445 1.12336 1.12336 0.37445 -b = -1.00000 1.16192 0.69594 0.13776 +n = 4; +wc = 0.3; +[b a] = butter(n, wc, "high") + ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/buttord.xml b/help/en_US/buttord.xml index da92712..32b7f21 100644 --- a/help/en_US/buttord.xml +++ b/help/en_US/buttord.xml @@ -17,7 +17,7 @@ <refnamediv> <refname>buttord</refname> - <refpurpose>/This function computes the minimum filter order of a Butterworth filter with the desired response characteristics.</refpurpose> + <refpurpose>Minimum filter order and 3dB cutoff frequency of a digital Butterworth filter with the desired response characteristics. </refpurpose> </refnamediv> @@ -33,38 +33,47 @@ <title>Parameters</title> <variablelist> <varlistentry><term>Wp:</term> - <listitem><para> scalar or vector of length 2</para></listitem></varlistentry> + <listitem><para> scalar or vector of length 2 (passband edge(s)), elements must be in the range [0,1]</para></listitem></varlistentry> <varlistentry><term>Ws:</term> - <listitem><para> scalar or vector of length 2, elements must be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> scalar or vector of length 2 (stopband edge(s)), elements must be in the range [0,1]</para></listitem></varlistentry> <varlistentry><term>Rp:</term> - <listitem><para> real or complex value</para></listitem></varlistentry> + <listitem><para> passband ripple in dB.</para></listitem></varlistentry> <varlistentry><term>Rs:</term> - <listitem><para> real or complex value</para></listitem></varlistentry> + <listitem><para> stopband attenuation in dB.</para></listitem></varlistentry> + <varlistentry><term>n:</term> + <listitem><para> Minimum filter order satisfying specs.</para></listitem></varlistentry> + <varlistentry><term>Wc:</term> + <listitem><para> 3dB cutoff frequency/frequencies.</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function computes the minimum filter order of a Butterworth filter with the desired response characteristics. -The filter frequency band edges are specified by the passband frequency wp and stopband frequency ws. -Frequencies are normalized to the Nyquist frequency in the range [0,1]. -Rp is measured in decibels and is the allowable passband ripple, and Rs is also in decibels and is the minimum attenuation in the stop band. -If ws>wp, the filter is a low pass filter. If wp>ws, the filter is a high pass filter. -If wp and ws are vectors of length 2, then the passband interval is defined by wp the stopband interval is defined by ws. -If wp is contained within the lower and upper limits of ws, the filter is a band-pass filter. If ws is contained within the lower and upper limits of wp the filter is a band-stop or band-reject filter. +This function computes the minimum filter order of a Butterworth filter with the desired response characteristics. </para> +<para>The filter frequency band edges are specified by the passband frequency wp and stopband frequency ws.</para> +<para>Frequencies are normalized to the Nyquist frequency in the range [0,1]. </para> +<para>Rp is measured in decibels and is the allowable passband ripple, and Rs is also in decibels and is the minimum attenuation in the stop band.</para> +<para>If ws>wp, the filter is a low pass filter. If wp>ws, the filter is a high pass filter.</para> +<para>If wp and ws are vectors of length 2, then the passband interval is defined by wp the stopband interval is defined by ws. </para> +<para>If wp is contained within the lower and upper limits of ws, the filter is a band-pass filter. If ws is contained within the lower and upper limits of wp the filter is a band-stop or band-reject filter. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -Wp = 40/500 -Ws = 150/500 -[n, Wn] = buttord(Wp, Ws, 3, 60) -n = 5 -Wn = 0.080038 + Wp = 40/500 ; + Ws = 150/500 ; + [n, Wc] = buttord(Wp, Ws, 3, 60) ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/cheb1ap.xml b/help/en_US/cheb1ap.xml index dbd541a..beae9a2 100644 --- a/help/en_US/cheb1ap.xml +++ b/help/en_US/cheb1ap.xml @@ -17,7 +17,7 @@ <refnamediv> <refname>cheb1ap</refname> - <refpurpose>This function designs a lowpass analog Chebyshev type I filter.</refpurpose> + <refpurpose>Produces a lowpass analog Chebyshev type I prototype filter.</refpurpose> </refnamediv> @@ -25,8 +25,6 @@ <title>Calling Sequence</title> <synopsis> [z, p, g] = cheb1ap (n, Rp) - [z, p] = cheb1ap (n, Rp) - p = cheb1ap (n, Rp) </synopsis> </refsynopsisdiv> @@ -36,7 +34,7 @@ <varlistentry><term>n:</term> <listitem><para> Filter Order</para></listitem></varlistentry> <varlistentry><term>Rp:</term> - <listitem><para> Peak-to-peak passband ripple</para></listitem></varlistentry> + <listitem><para> Peak-to-peak passband ripple in dB</para></listitem></varlistentry> <varlistentry><term>z:</term> <listitem><para> Zeros</para></listitem></varlistentry> <varlistentry><term>p:</term> @@ -49,27 +47,25 @@ <refsection> <title>Description</title> <para> -This is an Octave function. -It designs a lowpass analog Chebyshev type I filter of nth order and with a Peak-to-peak passband ripple of Rp. +It gives a lowpass analog Chebyshev type I prototype filter of nth order and with a Peak-to-peak passband ripple of Rp. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[z, p, g] = cheb1ap (10, 20) -z = [](0x0) -p = - -Columns 1 through 6: - --0.00157 - 0.98774i -0.00456 - 0.89105i -0.00709 - 0.70714i -0.00894 - 0.45401i -0.00991 - 0.15644i -0.00991 + 0.15644i - -Columns 7 through 10: - --0.00894 + 0.45401i -0.00709 + 0.70714i -0.00456 + 0.89105i -0.00157 + 0.98774i - -g = 1.9630e-04 - 6.3527e-22i +n = 10 ; +Rp = 3 ; +[z, p, g] = cheb1ap (n, Rp) ]]></programlisting> </refsection> + + <refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Sonu Sharma, RGIT Mumbai</member> + <member>FOSSEE, IIT Bombay</member> + </simplelist> + </refsection> + </refentry> diff --git a/help/en_US/cheb1ord.xml b/help/en_US/cheb1ord.xml index e60a114..843753c 100644 --- a/help/en_US/cheb1ord.xml +++ b/help/en_US/cheb1ord.xml @@ -17,7 +17,7 @@ <refnamediv> <refname>cheb1ord</refname> - <refpurpose>This function computes the minimum filter order of a Chebyshev type I filter with the desired response characteristics.</refpurpose> + <refpurpose>Minimum filter order of a digital Chebyshev type I filter with the desired response characteristics.</refpurpose> </refnamediv> @@ -25,7 +25,7 @@ <title>Calling Sequence</title> <synopsis> n = cheb1ord(Wp, Ws, Rp, Rs) - [n, Wc] = cheb1ord(Wp, Ws, Rp, Rs) + [n, Wp] = cheb1ord(Wp, Ws, Rp, Rs) </synopsis> </refsynopsisdiv> @@ -33,35 +33,48 @@ <title>Parameters</title> <variablelist> <varlistentry><term>Wp:</term> - <listitem><para> scalar or vector of length 2, all elements must be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> scalar or vector of length 2 (passband edge(s)), all elements must be in the range [0,1]</para></listitem></varlistentry> <varlistentry><term>Ws:</term> - <listitem><para> scalar or vector of length 2, all elements must be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> scalar or vector of length 2 (stopband edge(s)), all elements must be in the range [0,1]</para></listitem></varlistentry> <varlistentry><term>Rp:</term> - <listitem><para> real value</para></listitem></varlistentry> + <listitem><para> passband ripple in dB.</para></listitem></varlistentry> <varlistentry><term>Rs:</term> - <listitem><para> real value</para></listitem></varlistentry> + <listitem><para> stopband attenuation in dB.</para></listitem></varlistentry> + <varlistentry><term>n:</term> + <listitem><para> Minimum filter order satisfying specs.</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function computes the minimum filter order of a Chebyshev type I filter with the desired response characteristics. -Stopband frequency ws and passband frequency wp specify the the filter frequency band edges. -Frequencies are normalized to the Nyquist frequency in the range [0,1]. -Rp is measured in decibels and is the allowable passband ripple and Rs is also measured in decibels and is the minimum attenuation in the stop band. -If ws>wp then the filter is a low pass filter. If wp>ws, then the filter is a high pass filter. -If wp and ws are vectors of length 2, then the passband interval is defined by wp and the stopband interval is defined by ws. -If wp is contained within the lower and upper limits of ws, the filter is a band-pass filter. If ws is contained within the lower and upper limits of wp, the filter is a band-stop or band-reject filter. +This function computes the minimum filter order of a Chebyshev type I filter with the desired response characteristics. </para> +<para>Stopband frequency ws and passband frequency wp specify the the filter frequency band edges. </para> +<para>Frequencies are normalized to the Nyquist frequency in the range [0,1]. </para> +<para>Rp is measured in decibels and is the allowable passband ripple and Rs is also measured in decibels and is the minimum attenuation in the stop band.</para> +<para>If ws>wp then the filter is a low pass filter. If wp>ws, then the filter is a high pass filter.</para> +<para>If wp and ws are vectors of length 2, then the passband interval is defined by wp and the stopband interval is defined by ws. </para> +<para>If wp is contained within the lower and upper limits of ws, the filter is a band-pass filter. If ws is contained within the lower and upper limits of wp, the filter is a band-stop or band-reject filter. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -cheb1ord(0.1,0.2,-0.3,4) -ans = 2 +wp = [0.25 0.3]; +ws = [0.24 0.31]; +Rp = 3; +Rs = 10; +[n, wp]=cheb1ord(wp, ws, Rp, Rs) + ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/cheb2ap.xml b/help/en_US/cheb2ap.xml index 0fcdd8f..7035925 100644 --- a/help/en_US/cheb2ap.xml +++ b/help/en_US/cheb2ap.xml @@ -17,7 +17,7 @@ <refnamediv> <refname>cheb2ap</refname> - <refpurpose>This function designs a lowpass analog Chebyshev type II filter.</refpurpose> + <refpurpose>Produces a lowpass analog Chebyshev type II prototype filter.</refpurpose> </refnamediv> @@ -25,8 +25,6 @@ <title>Calling Sequence</title> <synopsis> [z, p, g] = cheb2ap (n, Rs) - [z, p] = cheb2ap (n, Rs) - p = cheb2ap (n, Rs) </synopsis> </refsynopsisdiv> @@ -36,7 +34,7 @@ <varlistentry><term>n:</term> <listitem><para> Filter Order</para></listitem></varlistentry> <varlistentry><term>Rs:</term> - <listitem><para> Stopband attenuation</para></listitem></varlistentry> + <listitem><para> Stopband attenuation in dB</para></listitem></varlistentry> <varlistentry><term>z:</term> <listitem><para> Zeros</para></listitem></varlistentry> <varlistentry><term>p:</term> @@ -49,15 +47,25 @@ <refsection> <title>Description</title> <para> -This is an Octave function. -This function designs a lowpass analog Chebyshev type II filter of nth order and with a stopband attenuation of Rs. +This function gives a lowpass analog Chebyshev type II prototpye filter of nth order and with a stopband attenuation of Rs. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ - +n = 4; +Rs = 10; +[z, p, g] = cheb2ap (n, Rs) ]]></programlisting> </refsection> + + <refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Sonu Sharma, RGIT Mumbai</member> + <member>FOSSEE, IIT Bombay</member> + </simplelist> + </refsection> + </refentry> diff --git a/help/en_US/cheb2ord.xml b/help/en_US/cheb2ord.xml index 199c595..279e258 100644 --- a/help/en_US/cheb2ord.xml +++ b/help/en_US/cheb2ord.xml @@ -17,7 +17,7 @@ <refnamediv> <refname>cheb2ord</refname> - <refpurpose>This function computes the minimum filter order of a Chebyshev type II filter with the desired response characteristics.</refpurpose> + <refpurpose>Minimum filter order of a digital Chebyshev type II filter with the desired response characteristics. </refpurpose> </refnamediv> @@ -25,7 +25,7 @@ <title>Calling Sequence</title> <synopsis> n = cheb2ord(Wp, Ws, Rp, Rs) - [n, Wc] = cheb2ord(Wp, Ws, Rp, Rs) + [n, Ws] = cheb2ord(Wp, Ws, Rp, Rs) </synopsis> </refsynopsisdiv> @@ -33,35 +33,47 @@ <title>Parameters</title> <variablelist> <varlistentry><term>Wp:</term> - <listitem><para> scalar or vector of length 2, all elements must be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> scalar or vector of length 2 (passband edge(s)), all elements must be in the range [0,1]</para></listitem></varlistentry> <varlistentry><term>Ws:</term> - <listitem><para> scalar or vector of length 2, all elements must be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> scalar or vector of length 2 (stopband edge(s)), all elements must be in the range [0,1]</para></listitem></varlistentry> <varlistentry><term>Rp:</term> - <listitem><para> real value</para></listitem></varlistentry> + <listitem><para> passband ripple in dB.</para></listitem></varlistentry> <varlistentry><term>Rs:</term> - <listitem><para> real value</para></listitem></varlistentry> + <listitem><para> stopband attenuation in dB.</para></listitem></varlistentry> + <varlistentry><term>n:</term> + <listitem><para> Minimum order of filter satisfying given specs.</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function computes the minimum filter order of a Chebyshev type II filter with the desired response characteristics. -Stopband frequency ws and passband frequency wp specify the the filter frequency band edges. -Frequencies are normalized to the Nyquist frequency in the range [0,1]. -Rp is measured in decibels and is the allowable passband ripple and Rs is also measured in decibels and is the minimum attenuation in the stop band. -If ws>wp then the filter is a low pass filter. If wp>ws, then the filter is a high pass filter. -If wp and ws are vectors of length 2, then the passband interval is defined by wp and the stopband interval is defined by ws. -If wp is contained within the lower and upper limits of ws, the filter is a band-pass filter. If ws is contained within the lower and upper limits of wp, the filter is a band-stop or band-reject filter. +This function computes the minimum filter order of a Chebyshev type II filter with the desired response characteristics.</para> +<para>Stopband frequency ws and passband frequency wp specify the the filter frequency band edges.</para> +<para>Frequencies are normalized to the Nyquist frequency in the range [0,1].</para> +<para>Rp is measured in decibels and is the allowable passband ripple and Rs is also measured in decibels and is the minimum attenuation in the stop band.</para> +<para>If ws>wp then the filter is a low pass filter. If wp>ws, then the filter is a high pass filter.</para> +<para>If wp and ws are vectors of length 2, then the passband interval is defined by wp and the stopband interval is defined by ws.</para> +<para>If wp is contained within the lower and upper limits of ws, the filter is a band-pass filter. If ws is contained within the lower and upper limits of wp, the filter is a band-stop or band-reject filter. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -cheb2ord([0.25,0.3],[0.2,0.8],0.3,0.4) -ans = 1 + Wp = 40/500; + Ws = 150/500; + Rp = 3; + Rs = 60; + [n,Ws] = cheb2ord(Wp,Ws,Rp,Rs) ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/cheby1.xml b/help/en_US/cheby1.xml index 92a7848..e33a506 100644 --- a/help/en_US/cheby1.xml +++ b/help/en_US/cheby1.xml @@ -17,20 +17,19 @@ <refnamediv> <refname>cheby1</refname> - <refpurpose>This function generates a Chebyshev type I filter with rp dB of passband ripple.</refpurpose> + <refpurpose>Chebyshev type I filter design with rp dB of passband ripple.</refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [a, b] = cheby1 (n, rp, w) - [a, b] = cheby1 (n, rp, w, "high") - [a, b] = cheby1 (n, rp, [wl, wh]) - [a, b] = cheby1 (n, rp, [wl, wh], "stop") - [a, b, c] = cheby1 (…) - [a, b, c, d] = cheby1 (…) - […] = cheby1 (…, "s") + [b, a] = cheby1 (n, rp, wp) + [b, a] = cheby1 (n, rp, wp, "high") + [b, a] = cheby1 (n, rp, [wl, wh]) + [b, a] = cheby1 (n, rp, [wl, wh], "stop") + [z, p, g] = cheby1 (…) + […] = cheby1 (…, "s") </synopsis> </refsynopsisdiv> @@ -38,37 +37,41 @@ <title>Parameters</title> <variablelist> <varlistentry><term>n:</term> - <listitem><para> positive integer value</para></listitem></varlistentry> + <listitem><para> positive integer value (order of filter)</para></listitem></varlistentry> <varlistentry><term>rp:</term> - <listitem><para> non negative scalar value</para></listitem></varlistentry> - <varlistentry><term>w:</term> - <listitem><para> vector, all elements must be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> non negative scalar value (passband ripple)</para></listitem></varlistentry> + <varlistentry><term>wp:</term> + <listitem><para> vector, all elements must be in the range [0,1]</para><para> 1).Normalised digital passband edge(s) for digital filter, in the range [0, 1] {dimensionless}</para><para> 2).Analog passband edge(s) for analog filter, in the range [0, Inf] {rad/sec}</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function generates a Chebyshev type I filter with rp dB of passband ripple. -The fourth parameter takes in high or low, default value is low. The cutoff is pi*Wc radians. -[b, a] = cheby1(n, Rp, [Wl, Wh]) indicates a band pass filter with edges pi*Wl and pi*Wh radians. -[b, a] = cheby1(n, Rp, [Wl, Wh], ’stop’) indicates a band reject filter with edges pi*Wl and pi*Wh radians. -[z, p, g] = cheby1(...) returns filter as zero-pole-gain rather than coefficients of the numerator and denominator polynomials. -[...] = cheby1(...,’s’) returns a Laplace space filter, w can be larger than 1. -[a,b,c,d] = cheby1(...) returns state-space matrices. +This function generates a Chebyshev type I filter with rp dB of passband ripple.</para> +<para>if third parameter is scalar the fourth parameter takes in high or low, default value is low. The cutoff is pi*Wc radians.</para> +<para>[b, a] = cheby1(n, Rp, [Wl, Wh]) indicates a band pass filter with edges pi*Wl and pi*Wh radians.</para> +<para>[b, a] = cheby1(n, Rp, [Wl, Wh], ’stop’) indicates a band reject filter with edges pi*Wl and pi*Wh radians.</para> +<para>[z, p, g] = cheby1(...) returns filter as zero-pole-gain rather than coefficients of the numerator and denominator polynomials.</para> +<para>[...] = cheby1(...,’s’) returns a Laplace space filter, w can be larger than 1 rad/sec. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[a,b,c]=cheby1(2,6,0.7,"high") -a = -1 1 -b = --0.62915 + 0.55372i -0.62915 - 0.55372i -c = 0.055649 +n = 2; +rp = 6; +wp = 0.7; +[z, p, k]=cheby1(n, rp, wp, "high") ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/cheby2.xml b/help/en_US/cheby2.xml index 24cef7d..7eb4fea 100644 --- a/help/en_US/cheby2.xml +++ b/help/en_US/cheby2.xml @@ -17,20 +17,19 @@ <refnamediv> <refname>cheby2</refname> - <refpurpose>This function generates a Chebyshev type II filter with rs dB of stopband attenuation.</refpurpose> + <refpurpose>Chebyshev type II filter design with rs dB of stopband attenuation.</refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [a, b] = cheby2 (n, rs, wc) - [a, b] = cheby2 (n, rs, wc, "high") - [a, b] = cheby2 (n, rs, [wl, wh]) - [a, b] = cheby2 (n, rs, [wl, wh], "stop") - [a, b, c] = cheby2 (…) - [a, b, c, d] = cheby2 (…) - […] = cheby2 (…, "s") + [b, a] = cheby2 (n, rs, ws) + [b, a] = cheby2 (n, rs, ws, "high") + [b, a] = cheby2 (n, rs, [wl, wh]) + [b, a] = cheby2 (n, rs, [wl, wh], "stop") + [z, p, g] = cheby2 (…) + […] = cheby2 (…, "s") </synopsis> </refsynopsisdiv> @@ -38,37 +37,42 @@ <title>Parameters</title> <variablelist> <varlistentry><term>n:</term> - <listitem><para> positive integer value</para></listitem></varlistentry> - <varlistentry><term>rp:</term> - <listitem><para> non negative scalar value</para></listitem></varlistentry> - <varlistentry><term>w:</term> - <listitem><para> vector, all elements must be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> positive integer value (order of filter)</para></listitem></varlistentry> + <varlistentry><term>rs:</term> + <listitem><para> non negative scalar value (stopband attenuation in dB)</para></listitem></varlistentry> + <varlistentry><term>ws:</term> + <listitem><para> vector, all elements must be in the range [0,1]</para><para> 1).Normalised digital stopband edge(s) for digital filter, in the range [0, 1] {dimensionless}</para><para> 2).Analog stopband edge(s) for analog filter, in the range [0, Inf] {rad/sec}</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function generates a Chebyshev type II filter with rs dB of stopband attenuation. -The fourth parameter takes in high or low, default value is low. The cutoff is pi*Wc radians. -[b, a] = cheby2(n, Rp, [Wl, Wh]) indicates a band pass filter with edges pi*Wl and pi*Wh radians. -[b, a] = cheby2(n, Rp, [Wl, Wh], ’stop’) indicates a band reject filter with edges pi*Wl and pi*Wh radians. -[z, p, g] = cheby2(...) returns filter as zero-pole-gain rather than coefficients of the numerator and denominator polynomials. -[...] = cheby2(...,’s’) returns a Laplace space filter, w can be larger than 1. -[a,b,c,d] = cheby2(...) returns state-space matrices. +This function generates a Chebyshev type II filter with rs dB of stopband attenuation.</para> +<para>If third parameter is scalar then,the fourth parameter takes in high or low, default value is low. The cutoff is pi*Wc radians.</para> +<para>[b, a] = cheby2(n, Rp, [Wl, Wh]) indicates a band pass filter with edges pi*Wl and pi*Wh radians.</para> +<para>[b, a] = cheby2(n, Rp, [Wl, Wh], ’stop’) indicates a band reject filter with edges pi*Wl and pi*Wh radians.</para> +<para>[z, p, g] = cheby2(...) returns filter as zero-pole-gain rather than coefficients of the numerator and denominator polynomials.</para> +<para>[...] = cheby2(...,’s’) returns a Laplace space filter, wp can be larger than 1 rad/sec. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[a,b,c]=cheby2(2,5,0.7,"high") -a = --0.31645 - 0.94861i -0.31645 + 0.94861i -b = --0.39388 + 0.53138i -0.39388 - 0.53138i -c = 0.47528 +n = 2; +rs = 5; +ws = 0.7; +[z, p, g]=cheby2(n, rs, ws, "high") + ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/chirp.xml b/help/en_US/chirp.xml index 31ccb71..60fc279 100644 --- a/help/en_US/chirp.xml +++ b/help/en_US/chirp.xml @@ -17,10 +17,9 @@ <refnamediv> <refname>chirp</refname> - <refpurpose>This function evaluates a chirp signal at time t.</refpurpose> + <refpurpose>Chirp signal at time t.</refpurpose> </refnamediv> - <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> @@ -28,8 +27,8 @@ y = chirp(t, f0) y = chirp(t, f0, t1) y = chirp(t, f0, t1, f1) - y = chirp(t, f0, t1, f1, frm) - y = chirp(t, f0, t1, f1, frm, phse) + y = chirp(t, f0, t1, f1, form) + y = chirp(t, f0, t1, f1, form, phase) </synopsis> </refsynopsisdiv> @@ -37,26 +36,27 @@ <title>Parameters</title> <variablelist> <varlistentry><term>t:</term> - <listitem><para> vector</para></listitem></varlistentry> + <listitem><para> a vector of times to evaluate the chirp signal.</para></listitem></varlistentry> <varlistentry><term>f0:</term> - <listitem><para> </para></listitem></varlistentry> + <listitem><para> the frequency at t=0. [default value = 0 Hz]</para></listitem></varlistentry> <varlistentry><term>t1:</term> - <listitem><para> </para></listitem></varlistentry> + <listitem><para> some intermediate time. [default value = 1 sec] </para></listitem></varlistentry> <varlistentry><term>f1:</term> - <listitem><para> </para></listitem></varlistentry> - <varlistentry><term>frm:</term> - <listitem><para> string value, takes in "linear", "quadratic", "logarithmic"</para></listitem></varlistentry> - <varlistentry><term>phse:</term> - <listitem><para> </para></listitem></varlistentry> + <listitem><para> frequency at t=t1. [default value = 100 Hz]</para></listitem></varlistentry> + <varlistentry><term>form:</term> + <listitem><para> string value, takes in "linear", "quadratic", "logarithmic". [default value = "linear"]</para></listitem></varlistentry> + <varlistentry><term>phase:</term> + <listitem><para> phase shift at t=0. [default value = 0]</para></listitem></varlistentry> + <varlistentry><term>y:</term> + <listitem><para> chirp signal value corresponding to t. </para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function evaluates a chirp signal at time t. A chirp signal is a frequency swept cosine wave. -The first argument is a vector of times to evaluate the chirp signal, second argument is the frequency at t=0, third argument is time t1 and fourth argument is frequency at t1. +This function evaluates a chirp signal at time t. A chirp signal is a frequency swept cosine wave.</para> +<para>The first argument is a vector of times to evaluate the chirp signal, second argument is the frequency at t=0, third argument is time t1 and fourth argument is frequency at t1. The fifth argument is the form which takes in values "linear", "quadratic" and "logarithmic", the sixth argument gives the phase shift at t=0. </para> </refsection> @@ -64,12 +64,20 @@ The fifth argument is the form which takes in values "linear", "quadratic" and " <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -chirp([4,3,2,1],4,5,0.9) -ans = -column 1 to 3 -0.9685832 0.2486899 0.0627905 -column 4 -- 0.3681246 + t = [4,3,2,1]; + f0 = 4; + t1 = 5; + f1 = 0.9; + form = "quadratic"; + y = chirp(t, f0, t1, f1, form) ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/circshift.xml b/help/en_US/circshift.xml new file mode 100644 index 0000000..d457205 --- /dev/null +++ b/help/en_US/circshift.xml @@ -0,0 +1,58 @@ +<?xml version="1.0" encoding="UTF-8"?> + +<!-- + * + * This help file was generated from circshift.sci using help_from_sci(). + * + --> + +<refentry version="5.0-subset Scilab" xml:id="circshift" xml:lang="en" + xmlns="http://docbook.org/ns/docbook" + xmlns:xlink="http://www.w3.org/1999/xlink" + xmlns:svg="http://www.w3.org/2000/svg" + xmlns:ns3="http://www.w3.org/1999/xhtml" + xmlns:mml="http://www.w3.org/1998/Math/MathML" + xmlns:scilab="http://www.scilab.org" + xmlns:db="http://docbook.org/ns/docbook"> + + <refnamediv> + <refname>circshift</refname> + <refpurpose>Shifts array/matrix circularly</refpurpose> + <para> </para> + </refnamediv> + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> +R = circshift(M, d) + </synopsis> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>M , R :</term> + <listitem><para> vector or matrix of any data type</para></listitem></varlistentry> + <varlistentry><term>d :</term> + <listitem><para> vector of integers. d(i) is the shift to be applied to the M's components along its ith dimension.</para>for example d = [0 n] will shift element n position along column<para></para></listitem></varlistentry> + </variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Description</title> + <para> +circularly shifts by d(i) positions components of M along its ith dimensions +</para> + <para> </para> +</refsection> + +<refsection> + <title>Example : 1</title> + <programlisting role="example"><![CDATA[ + M = [1 2 3 4]; + circshift(M, [0 1]) + ]]></programlisting> +</refsection> + +</refentry> diff --git a/help/en_US/dctmtx.xml b/help/en_US/dctmtx.xml index 0b05453..2594b48 100644 --- a/help/en_US/dctmtx.xml +++ b/help/en_US/dctmtx.xml @@ -17,14 +17,14 @@ <refnamediv> <refname>dctmtx</refname> - <refpurpose></refpurpose> + <refpurpose>Return the DCT transformation matrix of size N-by-N.</refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [y]=dctmtx(n) + T = dctmtx(n) </synopsis> </refsynopsisdiv> @@ -39,7 +39,6 @@ <refsection> <title>Description</title> <para> -This is an Octave function dctmtx(n) returns a Discrete cosine transform matrix of order n-by-n. It is useful for jpeg image compression. D*A is the DCT of the columns of A and D'*A is the inverse DCT of the columns of A (when A is n-by-n). </para> </refsection> @@ -47,12 +46,16 @@ dctmtx(n) returns a Discrete cosine transform matrix of order n-by-n. It is usef <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -1. dctmtx(2) -ans = [0.70711 0.70711; 0.70711 -0.70711] -2. dctmtx(3) -ans = [5.7735e-01 5.7735e-01 5.7735e-01; -7.0711e-01 4.9996e-17 -7.0711e-01; -4.0825e-01 -8.1650e-01 4.0825e-01] + n= 3; + T = dctmtx(n) ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/dftmtx.xml b/help/en_US/dftmtx.xml index ed6ecf7..4197d98 100644 --- a/help/en_US/dftmtx.xml +++ b/help/en_US/dftmtx.xml @@ -17,14 +17,14 @@ <refnamediv> <refname>dftmtx</refname> - <refpurpose></refpurpose> + <refpurpose>Computes n-by-n Discrete Fourier transformation matrix. </refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [d]=dftmtx(n) + d = dftmtx(n) </synopsis> </refsynopsisdiv> @@ -39,7 +39,6 @@ <refsection> <title>Description</title> <para> -This is an Octave function This fuction gives a complex matrix of values whose product with a vector produces the discrete Fourier transform. This can also be achieved by directly using the fft function i.e. y=fft(x) is same as y=A*x where A=dftmtx(n). </para> </refsection> @@ -47,10 +46,15 @@ This fuction gives a complex matrix of values whose product with a vector produc <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -1. dftmtx(3) -ans = 1.00000 + 0.00000i 1.00000 + 0.00000i 1.00000 + 0.00000i -1.00000 + 0.00000i -0.50000 - 0.86603i -0.50000 + 0.86603i -1.00000 - 0.00000i -0.50000 + 0.86603i -0.50000 - 0.86603i +d = dftmtx(4) ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/digitrevorder.xml b/help/en_US/digitrevorder.xml new file mode 100644 index 0000000..988f372 --- /dev/null +++ b/help/en_US/digitrevorder.xml @@ -0,0 +1,63 @@ +<?xml version="1.0" encoding="UTF-8"?> + +<!-- + * + * This help file was generated from digitrevorder.sci using help_from_sci(). + * + --> + +<refentry version="5.0-subset Scilab" xml:id="digitrevorder" xml:lang="en" + xmlns="http://docbook.org/ns/docbook" + xmlns:xlink="http://www.w3.org/1999/xlink" + xmlns:svg="http://www.w3.org/2000/svg" + xmlns:ns3="http://www.w3.org/1999/xhtml" + xmlns:mml="http://www.w3.org/1998/Math/MathML" + xmlns:scilab="http://www.scilab.org" + xmlns:db="http://docbook.org/ns/docbook"> + + <refnamediv> + <refname>digitrevorder</refname> + <refpurpose></refpurpose> + </refnamediv> + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> + [y,i] = digitrevorder(x,r) + y = digitrevorder(x,r) + </synopsis> + <para> </para> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>x:</term> + <listitem><para> Vector of real or complex values</para></listitem></varlistentry> + <varlistentry><term>r:</term> + <listitem><para> radix / base </para></listitem></varlistentry> + <varlistentry><term>y:</term> + <listitem><para> input vector in bit reverse order</para></listitem></varlistentry> + <varlistentry><term>i:</term> + <listitem><para> indices after bit reversing </para></listitem></varlistentry> + <para> </para> + </variablelist> +</refsection> + +<refsection> + <title>Description</title> + <para> +This function returns the input data after reversing the digits of the indices and reordering the elements of the input array. +</para> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +x = [%i,1,3,6*%i] ; +r = 2 ; +[y i]=digitrevorder(x, r) + ]]></programlisting> +</refsection> + +</refentry> diff --git a/help/en_US/ellip.xml b/help/en_US/ellip.xml index 847f91e..66ec6fc 100644 --- a/help/en_US/ellip.xml +++ b/help/en_US/ellip.xml @@ -17,20 +17,19 @@ <refnamediv> <refname>ellip</refname> - <refpurpose>This function generates an elliptic or Cauer filter with rp dB of passband ripple and rs dB of stopband attenuation.</refpurpose> + <refpurpose>Elliptic/Cauer filter design with rp dB of passband ripple and rs dB of stopband attenuation.</refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [a, b] = ellip (n, rp, rs, wp) - [a, b] = ellip (n, rp, rs, wp, "high") - [a, b] = ellip (n, rp, rs, [wl, wh]) - [a, b] = ellip (n, rp, rs, [wl, wh], "stop") - [a, b, c] = ellip (…) - [a, b, c, d] = ellip (…) - […] = ellip (…, "s") + [b, a] = ellip (n, rp, rs, wp) + [b, a] = ellip (n, rp, rs, wp, "high") + [b, a] = ellip (n, rp, rs, [wl, wh]) + [b, a] = ellip (n, rp, rs, [wl, wh], "stop") + [z, p, g] = ellip (…) + […] = ellip (…, "s") </synopsis> </refsynopsisdiv> @@ -38,37 +37,36 @@ <title>Parameters</title> <variablelist> <varlistentry><term>n:</term> - <listitem><para> positive integer value</para></listitem></varlistentry> + <listitem><para> positive integer value (order of filter)</para></listitem></varlistentry> <varlistentry><term>rp:</term> - <listitem><para> non negative scalar value</para></listitem></varlistentry> + <listitem><para> non negative scalar value (passband ripple)</para></listitem></varlistentry> <varlistentry><term>rs:</term> - <listitem><para> non negative scalar value</para></listitem></varlistentry> - <varlistentry><term>w:</term> - <listitem><para> scalar or vector, all elements should be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> non negative scalar value (stopband attenuation)</para></listitem></varlistentry> + <varlistentry><term>ws:</term> + <listitem><para> scalar or vector of length 2, all elements should be in the range [0,1]</para><para> 1).Normalised digital passband edge(s) for digital filter, in the range [0, 1] {dimensionless}</para><para> 2).Analog passband edge(s) for analog filter, in the range [0, Inf] {rad/sec}</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function generates an elliptic or Cauer filter with rp dB of passband ripple and rs dB of stopband attenuation. -[b, a] = ellip(n, Rp, Rs, Wp) indicates low pass filter with order n, Rp decibels of ripple in the passband and a stopband Rs decibels down and cutoff of pi*Wp radians. If the fifth argument is high, then the filter is a high pass filter. -[b, a] = ellip(n, Rp, Rs, [Wl, Wh]) indictaes band pass filter with band pass edges pi*Wl and pi*Wh. If the fifth argument is stop, the filter is a band reject filter. -[z, p, g] = ellip(...) returns filter as zero-pole-gain. -[...] = ellip(...,’s’) returns a Laplace space filter, w can be larger than 1. -[a, b, c, d] = ellip(...) returns state-space matrices. +This function generates an elliptic or Cauer filter with rp dB of passband ripple and rs dB of stopband attenuation.</para> +<para>[b, a] = ellip(n, Rp, Rs, Wp) indicates low pass filter with order n, Rp decibels of ripple in the passband and a stopband Rs decibels down and cutoff of pi*Wp radians. If the fifth argument is high, then the filter is a high pass filter.</para> +<para>[b, a] = ellip(n, Rp, Rs, [Wl, Wh]) indictaes band pass filter with band pass edges pi*Wl and pi*Wh. If the fifth argument is stop, the filter is a band reject filter.</para> +<para>[b,a] = ellip(n, Rp, Rs, [Wl, Wh], 'stop') band reject filter with edges pi*Wl and pi*Wh</para> +<para>[z, p, g] = ellip(...) returns filter as zero-pole-gain.</para> +<para>[...] = ellip(...,’s’) returns a Laplace space filter, wp can be larger than 1 rad/sec. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[a,b]=ellip(2, 0.5, 0.7, [0.3,0.4]) -a = -0.88532 -1.58410 2.40380 -1.58410 0.88532 -b = -1.00000 -1.78065 2.68703 -1.75725 0.97454 +n = 2; +rp = 3; +rs = 40; +wp = [0.3 0.4]; +[b, a]=ellip(n, rp, rs, wp) ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/ellipap.xml b/help/en_US/ellipap.xml index 597a4c1..b0cc2fb 100644 --- a/help/en_US/ellipap.xml +++ b/help/en_US/ellipap.xml @@ -17,7 +17,7 @@ <refnamediv> <refname>ellipap</refname> - <refpurpose>Designs a lowpass analog elliptic filter.</refpurpose> + <refpurpose>Produces a lowpass analog elliptic prototype filter.</refpurpose> </refnamediv> @@ -25,8 +25,6 @@ <title>Calling Sequence</title> <synopsis> [z, p, g] = ellipap (n, Rp, Rs) - [z, p] = ellipap (n, Rp, Rs) - z = ellipap (n, Rp, Rs) </synopsis> </refsynopsisdiv> @@ -36,33 +34,41 @@ <varlistentry><term>n:</term> <listitem><para> Filter Order</para></listitem></varlistentry> <varlistentry><term>Rp:</term> - <listitem><para> Peak-to-peak passband ripple</para></listitem></varlistentry> + <listitem><para> Peak-to-peak passband ripple in dB</para></listitem></varlistentry> <varlistentry><term>Rs:</term> - <listitem><para> Stopband attenuation</para></listitem></varlistentry> + <listitem><para> Stopband attenuation in dB</para></listitem></varlistentry> + <varlistentry><term>z:</term> + <listitem><para> Zeros</para></listitem></varlistentry> + <varlistentry><term>p:</term> + <listitem><para> Poles</para></listitem></varlistentry> + <varlistentry><term>g:</term> + <listitem><para> Gain</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -It designs a lowpass analog elliptic filter of nth order, with a Peak-to-peak passband ripple of Rp and a stopband attenuation of Rs. +It gives a lowpass analog elliptic prototype filter of nth order, with a Peak-to-peak passband ripple of Rp dB and a stopband attenuation of Rs dB. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[z, p, g] = ellipap (5, 10, 10) -z = - -0.0000 + 2.5546i 0.0000 + 1.6835i -0.0000 - 2.5546i -0.0000 - 1.6835i - -p = - --0.05243 + 0.63524i -0.01633 + 0.96289i -0.05243 - 0.63524i -0.01633 - 0.96289i -0.07369 + 0.00000i - -g = 0.0015012 +n = 4; +Rp = 3; +Rs = 10; +[z, p, g] = ellipap (n, Rp, Rs) ]]></programlisting> </refsection> + + <refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Sonu Sharma, RGIT Mumbai</member> + <member>FOSSEE, IIT Bombay</member> + </simplelist> + </refsection> + </refentry> diff --git a/help/en_US/ellipord.xml b/help/en_US/ellipord.xml index 0f562c8..2a3dbe2 100644 --- a/help/en_US/ellipord.xml +++ b/help/en_US/ellipord.xml @@ -17,14 +17,14 @@ <refnamediv> <refname>ellipord</refname> - <refpurpose>This function computes the minimum filter order of an elliptic filter with the desired response characteristics.</refpurpose> + <refpurpose>Minimum filter order of a digital elliptic/Cauer filter with the desired response characteristics. </refpurpose> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [n] = ellipord(Wp, Ws, Rp, Rs) + n = ellipord(Wp, Ws, Rp, Rs) [n, Wp] = ellipord(Wp, Ws, Rp, Rs) </synopsis> </refsynopsisdiv> @@ -33,36 +33,39 @@ <title>Parameters</title> <variablelist> <varlistentry><term>Wp:</term> - <listitem><para> scalar or vector of length 2, all elements must be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> scalar or vector of length 2 (passband edge(s)), all elements must be in the range [0,1]</para></listitem></varlistentry> <varlistentry><term>Ws:</term> - <listitem><para> scalar or vector of length 2, all elements must be in the range [0,1]</para></listitem></varlistentry> + <listitem><para> scalar or vector of length 2 (stopband edge(s)), all elements must be in the range [0,1]</para></listitem></varlistentry> <varlistentry><term>Rp:</term> - <listitem><para> real or complex value</para></listitem></varlistentry> + <listitem><para> passband ripple in dB.</para></listitem></varlistentry> <varlistentry><term>Rs:</term> - <listitem><para> real or complex value</para></listitem></varlistentry> + <listitem><para> stopband attenuation in dB.</para></listitem></varlistentry> + <varlistentry><term>n:</term> + <listitem><para> Minimum order of filter satisfying given specs.</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -This function computes the minimum filter order of an elliptic filter with the desired response characteristics. -Stopband frequency ws and passband frequency wp specify the the filter frequency band edges. -Frequencies are normalized to the Nyquist frequency in the range [0,1]. -Rp is measured in decibels and is the allowable passband ripple and Rs is also measured in decibels and is the minimum attenuation in the stop band. -If ws>wp then the filter is a low pass filter. If wp>ws, then the filter is a high pass filter. -If wp and ws are vectors of length 2, then the passband interval is defined by wp and the stopband interval is defined by ws. -If wp is contained within the lower and upper limits of ws, the filter is a band-pass filter. If ws is contained within the lower and upper limits of wp, the filter is a band-stop or band-reject filter. +This function computes the minimum filter order of an elliptic filter with the desired response characteristics.</para> +<para>Stopband frequency ws and passband frequency wp specify the the filter frequency band edges.</para> +<para>Frequencies are normalized to the Nyquist frequency in the range [0,1].</para> +<para>Rp is measured in decibels and is the allowable passband ripple and Rs is also measured in decibels and is the minimum attenuation in the stop band.</para> +<para>If ws>wp then the filter is a low pass filter. If wp>ws, then the filter is a high pass filter.</para> +<para>If wp and ws are vectors of length 2, then the passband interval is defined by wp and the stopband interval is defined by ws.</para> +<para>If wp is contained within the lower and upper limits of ws, the filter is a band-pass filter. If ws is contained within the lower and upper limits of wp, the filter is a band-stop or band-reject filter. </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[a,b]=ellipord(0.2, 0.5, 0.7, 0.4) -a = 1 -b = 0.20000 + Wp = [60 200]/500; + Ws = [50 250]/500; + Rp = 3; + Rs = 40; + [n,Wp] = ellipord(Wp,Ws,Rp,Rs) ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/isfir.xml b/help/en_US/isfir.xml index 7aa7e0d..5974df7 100644 --- a/help/en_US/isfir.xml +++ b/help/en_US/isfir.xml @@ -17,7 +17,60 @@ <refnamediv> <refname>isfir</refname> - <refpurpose>[nargout,nargin]=argn();</refpurpose> + <refpurpose> Determines whether given system function is FIR or not</refpurpose> + <para> </para> </refnamediv> + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> + fir = isfir(b,a) + fir = isfir(sos) + </synopsis> + <para> </para> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>b</term> + <listitem><para> Coefficients of numerator polynomial of system function </para></listitem></varlistentry> + <varlistentry><term>a</term> + <listitem><para> Coefficients of denumerator polynomial of system function</para></listitem></varlistentry> + <varlistentry><term>sos</term> + <listitem><para> Second order section matrix of order Kx6 </para></listitem></varlistentry> + <varlistentry><term>fir</term> + <listitem><para> This function returns logical 1 if system is FIR (fir = 1) </para> <para> Otherwise it returns logical 0 (fir = 0)</para></listitem></varlistentry> + </variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Description</title> + <para> This function takes input a System function in terms of numerator and denumerator coefficients or in second order section (sos) matrix and checks for system having Finite Impulse Response (FIR) or not </para> +<para> </para> +</refsection> + +<refsection> + <title>Examples</title> + <para>Checking given system function is FIR or not</para> + <para> + <latex> + \begin{eqnarray} + H(z) = 1 - z^{-1} + z^{-2} + \end{eqnarray} + </latex> + </para> + <para> </para> + + <programlisting role="example"><![CDATA[ +b = [1 -1 1] ; +a = 1 ; +f = isfir(b,a) //This is an example of FIR system function, hence output will be f = 1 +]]></programlisting> +</refsection> + + + </refentry> diff --git a/help/en_US/islinphase.xml b/help/en_US/islinphase.xml index 54ba2d7..47e4407 100644 --- a/help/en_US/islinphase.xml +++ b/help/en_US/islinphase.xml @@ -17,7 +17,62 @@ <refnamediv> <refname>islinphase</refname> - <refpurpose>[nargout,nargin]=argn();</refpurpose> + <refpurpose>Checks given system function is linearphase or not</refpurpose> + <para> </para> </refnamediv> +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> + flag = islinphase(b,a) + flag = islinphase(sos) + flag = islinphase(...,tol) + </synopsis> + <para> </para> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>b</term> + <listitem><para> Coefficients of numerator polynomial of system function </para></listitem></varlistentry> + <varlistentry><term>a</term> + <listitem><para> Coefficients of denumerator polynomial of system function</para></listitem></varlistentry> + <varlistentry><term>sos</term> + <listitem><para> Second order section matrix of order Kx6 </para></listitem></varlistentry> + <varlistentry><term>tol</term> + <listitem><para> Tolerence in similarities between two numbers in phase response </para></listitem></varlistentry> + <varlistentry><term>flag</term> + <listitem><para> This function returns logical 1 if system is linear phase (flag = 1) </para> <para> Otherwise it returns logical 0 (flag = 0)</para></listitem></varlistentry> + </variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Description</title> + <para> This function takes input a System function in terms of numerator and denumerator coefficients or in second order section (sos) matrix and checks for system having Linear Phase Response or not </para> + <para> </para> +</refsection> + +<refsection> + <title>Examples</title> + + <para>Checking given system function is linear-phase or not</para> + <para> + <latex> + \begin{eqnarray} + H(z) = z^{-1} + 2 z^{-2} + 2 z^{-3} + z^{-4} + \end{eqnarray} + </latex> + </para> + <para> </para> + + <programlisting role="example"><![CDATA[ +b = [0 1 2 2 1 0] ; //Numerator polynomial coefficients +a = 1 ; //Denumerator polynomial coefficients +flag = islinphase(b,a) //This is an example of Symmetric FIR Filter which is Linear Phase, hence it will give output : flag = 1 +]]></programlisting> +</refsection> + + </refentry> diff --git a/help/en_US/ismaxphase.xml b/help/en_US/ismaxphase.xml index 67b480d..f3b3d65 100644 --- a/help/en_US/ismaxphase.xml +++ b/help/en_US/ismaxphase.xml @@ -17,7 +17,61 @@ <refnamediv> <refname>ismaxphase</refname> - <refpurpose>[nargout,nargin]=argn();</refpurpose> + <refpurpose>Checks given system function is Maximum-Phase system or not</refpurpose> + <para> </para> </refnamediv> + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> +flag = ismaxphase(b,a) +flag = ismaxphase(sos) +flag = ismaxphase(...,tol) + </synopsis> + <para> </para> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>b</term> + <listitem><para> Coefficients of numerator polynomial of system function </para></listitem></varlistentry> + <varlistentry><term>a</term> + <listitem><para> Coefficients of denumerator polynomial of system function</para></listitem></varlistentry> + <varlistentry><term>sos</term> + <listitem><para> Second order section matrix of order Kx6 </para></listitem></varlistentry> + <varlistentry><term>tol</term> + <listitem><para> Tolerence in similarities between two numbers in phase response </para></listitem></varlistentry> + <varlistentry><term>flag</term> + <listitem><para> This function returns logical 1 if system is maximum-phase system (flag = 1) </para> <para> Otherwise it returns logical 0 (flag = 0)</para></listitem></varlistentry> + </variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Description</title> + <para> This function determines whether the given system function is maximum-phase system or not . Maximum-phase system means all zeros of transfer function will be outside the unit circle in z-plane, also poles must be within unit circle for stability and causality </para> + <para> </para> +</refsection> + +<refsection> + <title>Examples</title> + + <para>Checking given system function is maximum phase system or not</para> + <para> + <latex> + \begin{eqnarray} + H(z) = 1 -5z^{-1} + 6 z^{-2} + \end{eqnarray} + </latex> + </para> + <para> </para> + <programlisting role="example"><![CDATA[ +b = [1 -5 6] ; //Numerator polynomial coefficients +a = 1 ; //Denumerator polynomial coefficients +flag = ismaxphase(b,a) //This is an example of Maximum-Phase system, hence it will give output as : flag = 1 +]]></programlisting> +</refsection> + </refentry> diff --git a/help/en_US/isminphase.xml b/help/en_US/isminphase.xml index f395fbe..40eef06 100644 --- a/help/en_US/isminphase.xml +++ b/help/en_US/isminphase.xml @@ -17,7 +17,61 @@ <refnamediv> <refname>isminphase</refname> - <refpurpose>[nargout,nargin]=argn();</refpurpose> + <refpurpose>Checks given system function is Maximum-Phase system or not</refpurpose> + <para> </para> </refnamediv> +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> +flag = ismaxphase(b,a) +flag = ismaxphase(sos) +flag = ismaxphase(...,tol) + </synopsis> + <para> </para> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>b</term> + <listitem><para> Coefficients of numerator polynomial of system function </para></listitem></varlistentry> + <varlistentry><term>a</term> + <listitem><para> Coefficients of denumerator polynomial of system function</para></listitem></varlistentry> + <varlistentry><term>sos</term> + <listitem><para> Second order section matrix of order Kx6 </para></listitem></varlistentry> + <varlistentry><term>tol</term> + <listitem><para> Tolerence in similarities between two numbers in phase response </para></listitem></varlistentry> + <varlistentry><term>flag</term> + <listitem><para> This function returns logical 1 if system is minimum-phase system (flag = 1) </para> <para> Otherwise it returns logical 0 (flag = 0)</para></listitem></varlistentry> + </variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Description</title> + <para> This function determines whether the given system function is minimum-phase system or not . Minimum-phase system means all zeros of transfer function will be inside the unit circle in z-plane,also poles must be within unit circle for stability and causality </para> + <para> </para> +</refsection> + +<refsection> + <title>Examples</title> + + <para>Checking given system function is minimum phase system or not</para> + <para> + <latex> + \begin{eqnarray} + H(z) = 1 -0.3z^{-1} + 0.02 z^{-2} + \end{eqnarray} + </latex> + </para> + <para> </para> + + <programlisting role="example"><![CDATA[ +b = [1 -0.3 0.02] ; //Numerator polynomial coefficients +a = 1 ; //Denumerator polynomial coefficients +flag = isminphase(b,a) //This is an example of Minimum-Phase system, hence it will give output as : flag = 1 +]]></programlisting> +</refsection> + </refentry> diff --git a/help/en_US/isstable.xml b/help/en_US/isstable.xml index 295c1d4..9b53add 100644 --- a/help/en_US/isstable.xml +++ b/help/en_US/isstable.xml @@ -17,7 +17,75 @@ <refnamediv> <refname>isstable</refname> - <refpurpose>SOS matrix corresponds to [bi(1) bi(2) bi(3) ai(1) ai(2) ai(3)].</refpurpose> + <refpurpose>Checks stability of given Discrete time system function</refpurpose> + <para> </para> </refnamediv> +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> +flag = ismaxphase(b,a) +flag = ismaxphase(sos) + </synopsis> + <para> </para> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>b</term> + <listitem><para> Coefficients of numerator polynomial of system function </para></listitem></varlistentry> + <varlistentry><term>a</term> + <listitem><para> Coefficients of denumerator polynomial of system function</para></listitem></varlistentry> + <varlistentry><term>sos</term> + <listitem><para> Second order section matrix of order Kx6 </para></listitem></varlistentry> + <varlistentry><term>flag</term> + <listitem><para> This function returns logical 1 if system is Stable (flag = 1) </para> <para> Otherwise it returns logical 0 (flag = 0)</para></listitem></varlistentry> + </variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Description</title> + <para> This function determines whether the given system function is Stable system function or not. Stable system means all poles of transfer function will be inside the unit circle in z-plane </para> + <para> </para> +</refsection> + +<refsection> + <title>Example : 1 <para>Example of stable system function </para> </title> + <para> + <latex> + \begin{eqnarray} + H(z) = \frac{1 +2z^{-1} } {1 -0.7z^{-1} + 0.1 z^{-2} } + \end{eqnarray} + </latex> + </para> + <para> </para> + + <programlisting role="example"><![CDATA[ +b = [1 2] ; //Numerator polynomial coefficients +a = [1 -0.7 0.1] ; //Denumerator polynomial coefficients +flag = isstable(b,a) //This is an example of Stable system, hence it will give output as : flag = 1 +]]></programlisting> +</refsection> + +<refsection> +<title> Example : 2 <para>Example of unstable system function</para> </title> + + <para> + <latex> + \begin{eqnarray} + H(z) = \frac{1 +2z^{-1} } {1 +5z^{-1} + 6z^{-2} } + \end{eqnarray} + </latex> + </para> + <para> </para> + + <programlisting role="example"><![CDATA[ +b = [1 2] ; //Numerator polynomial coefficients +a = [1 5 6] ; //Denumerator polynomial coefficients +flag = isstable(b,a) //This is an example of Unstable system, hence it will give output as : flag = 0 +]]></programlisting> +</refsection> + </refentry> diff --git a/help/en_US/kaiser.xml b/help/en_US/kaiser.xml index 394119b..32afa90 100644 --- a/help/en_US/kaiser.xml +++ b/help/en_US/kaiser.xml @@ -53,14 +53,9 @@ The second parameter gives the stop band attenuation of the Fourier transform of <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -kaiser(6,0.2) -ans = -0.9900745 -0.9964211 -0.9996020 -0.9996020 -0.9964211 -0.9900745 +L = 6 ; +beta = 0.2 ; +kaiser(L, beta) ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/lar2rc.xml b/help/en_US/lar2rc.xml index 5f07b8d..4a40678 100644 --- a/help/en_US/lar2rc.xml +++ b/help/en_US/lar2rc.xml @@ -17,7 +17,8 @@ <refnamediv> <refname>lar2rc</refname> - <refpurpose></refpurpose> + <refpurpose> Log Area Ratio to Reflection Coefficient</refpurpose> + <para> </para> </refnamediv> @@ -26,6 +27,7 @@ <synopsis> k = lar2rc(g) </synopsis> + <para> </para> </refsynopsisdiv> <refsection> @@ -36,16 +38,21 @@ <varlistentry><term>k:</term> <listitem><para> returns the reflection coefficients.</para></listitem></varlistentry> </variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Description</title> + <para> This function takes input as a vector of log area ratios and returns vector of reflection coefficients corresponding to log area ratio vector </para> + <para> </para> </refsection> <refsection> <title>Examples</title> + <para> </para> <programlisting role="example"><![CDATA[ -X = [7 6 5 8 3 6 8 7 5 2 4 7 4 3 2 5 4 9 5 3 5 7 3 9 4 1 2 0 5 4 8 6 4 6 5 3]; -k = lar2rc(X) -or t=[2 5 6; 8 6 5; 8 9 4] -k = lar2rc(t) - +g = [0.6389 4.5989 0.0063 0.0163 -0.0163]; //log area ratio inputs +k = lar2rc(g) // returns reflection coefficients corresponding to log area ratios ]]></programlisting> </refsection> @@ -57,4 +64,5 @@ k = lar2rc(t) <member><link linkend="Modified">to match MATLAB o/p when i/p is of type char and is a string by Debdeep Dey</link></member> </simplelist> </refsection> + </refentry> diff --git a/help/en_US/levinson.xml b/help/en_US/levinson.xml index 056795f..ac340a6 100644 --- a/help/en_US/levinson.xml +++ b/help/en_US/levinson.xml @@ -17,7 +17,81 @@ <refnamediv> <refname>levinson</refname> - <refpurpose></refpurpose> + <refpurpose>Levinson-Durbin Recurssion Algorithm</refpurpose> + <para> </para> </refnamediv> + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> +a = levinson(r) +a = levinson(r,n) +[a,e] = levinson(r,n) +[a,e,k] = levinson(r,n) + </synopsis> + <para> </para> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>r</term> + <listitem><para> Real or complex deterministic autocorrelation sequence input </para></listitem></varlistentry> + <varlistentry><term>a</term> + <listitem><para> Coefficients of length(r)-1 order Autoregressive linear process </para></listitem></varlistentry> + <varlistentry><term>n</term> + <listitem><para> Order of autoregressive model (default value is length(r)-1 , if n is not given)</para></listitem></varlistentry> + <varlistentry><term>e</term> + <listitem><para> Prediction error of order n</para></listitem></varlistentry> + <varlistentry><term>k</term> + <listitem><para> Reflection coefficient vector of length n</para></listitem></varlistentry> + </variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Description</title> + <para> The Levinson-Durbin recursion algorithm is used for finding an all-pole IIR filter with a given deterministic autocorrelation sequence (r) </para> + + <para> + <latex> + \begin{eqnarray} + H(z) = \frac{1}{1+a(2)z^{-1}+a(3)z^{-2} + ... +a(n+1)z^{-n}} + \end{eqnarray} + </latex> + </para> + + <para> </para> +</refsection> + +<refsection> + <title>Examples </title> + <para> Estimate the coefficients of an autoregressive process given by equation </para> + + <para> + <latex> + \begin{eqnarray} + x(n) = 0.1x(n-1) - 0.8x(n-2) + w(n) + \end{eqnarray} + </latex> + </para> + <para> </para> + + <programlisting role="example"><![CDATA[ + +a = [1 0.1 -0.8]; + +v = 0.4; //variance, v=0.4 +w = sqrt(v)*rand(15000,1,"normal"); +x = filter(1,a,w); + +[r,lg] = xcorr(x,'biased'); +r(lg<0) = []; + +ar = levinson(r,length(a)-1) //coefficients of autoregressive process + +]]></programlisting> +</refsection> + </refentry> diff --git a/help/en_US/lpc.xml b/help/en_US/lpc.xml index 1ebe531..079923e 100644 --- a/help/en_US/lpc.xml +++ b/help/en_US/lpc.xml @@ -18,6 +18,7 @@ <refnamediv> <refname>lpc</refname> <refpurpose>Linear prediction filter coefficients</refpurpose> + <para> </para> </refnamediv> @@ -26,9 +27,8 @@ <synopsis> [a,g] = lpc(x) [a,g] = lpc(x,p) - - </synopsis> + <para> </para> </refsynopsisdiv> <refsection> @@ -36,44 +36,71 @@ <para> [a,g] = lpc(x,p) Determines the coefficients of a pth order forward linear predictor -filter by minimizing the squared error. If p is unspecified, a -default value of length(x)-1 is used. +filter by minimizing the squared error. <para>If p is unspecified, a +default value of length(x)-1 is used.</para> </para> - <para> -</para> + <para> </para> </refsection> <refsection> <title>Parameters</title> <variablelist> <varlistentry><term>x:</term> - <listitem><para> double</para></listitem></varlistentry> + <listitem><para> double</para><para>input signal, if it is a matrix each column is computed independently</para></listitem></varlistentry> <varlistentry><term>p:</term> - <listitem><para> int, natural number, scalar</para></listitem></varlistentry> + <listitem><para> int, natural number, scalar</para><para>order of linear predictor filter, value must be scalar, positive and must be less than or equal to length of input signal </para></listitem></varlistentry> <varlistentry><term>a:</term> - <listitem><para> double</para></listitem></varlistentry> + <listitem><para> double</para><para>coefficient of forward linear predictor, coefficient for each signal input is returned as a row vector</para></listitem></varlistentry> <varlistentry><term>g:</term> - <listitem><para> double</para></listitem></varlistentry> + <listitem><para> double</para><para>Column vector of averaged square prediction error</para></listitem></varlistentry> </variablelist> </refsection> <refsection> + <title>Description</title> + <para> This function determines coefficients of a forward linear predictor by minimizing prediction error in least squares sense. It is used in Digital Filter Design </para> + <para> </para> +</refsection> + +<refsection> <title>Examples</title> - <programlisting role="example"><![CDATA[ -1) -noise = randn(20000,1); -x = filter(1,[1 1/5 1/3 1/4],noise); -x = x(15904:20000); -[a,g] = lpc(x,3); + <programlisting role="example"><![CDATA[ +noise = rand(50000,1,"normal"); //Gaussian White Noise +x = filter(1,[1 1/2 1/3 1/4],noise); +x = x(45904:50000); +[a,g]= lpc(x,3) +est_x = filter([0 -a(2:$)],1,x); +e = x-est_x; +[acs,lags] = xcorr(e,'coeff'); +plot(1:97,x(4001:4097),1:97,est_x(4001:4097),'--'); +a = gca(); +a.grid = [1,1]; +title 'Original Signal vs. LPC Estimate'; +xlabel 'Sample number', ylabel 'Amplitude'; +legend('Original signal','LPC estimate'); + ]]></programlisting> -References -[1] Hayes, Monson H. Statistical digital signal processing and modeling. -John Wiley & Sons, 2009, pg. 220 + <scilab:image> +noise = rand(50000,1,"normal"); //Gaussian White Noise +x = filter(1,[1 1/2 1/3 1/4],noise); +x = x(45904:50000); +[a,g]= lpc(x,3) +est_x = filter([0 -a(2:$)],1,x); +e = x-est_x; +[acs,lags] = xcorr(e,'coeff'); +plot(1:97,x(4001:4097),1:97,est_x(4001:4097),'--'); +a = gca(); +a.grid = [1,1]; +title 'Original Signal vs. LPC Estimate'; +xlabel 'Sample number', ylabel 'Amplitude'; +legend('Original signal','LPC estimate'); + </scilab:image> + <para> </para> - ]]></programlisting> </refsection> + <refsection> <title>See also</title> <simplelist type="inline"> diff --git a/help/en_US/medfilt1.xml b/help/en_US/medfilt1.xml index 2766e88..2760fe9 100644 --- a/help/en_US/medfilt1.xml +++ b/help/en_US/medfilt1.xml @@ -18,68 +18,107 @@ <refnamediv> <refname>medfilt1</refname> <refpurpose>1D median filtering</refpurpose> + <para> </para> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> + y = medfilt1(x) + y = medfilt1(x, n) + y = medfilt1(x, n, dim) + y = medfitl1(__, nanflag, padding) </synopsis> + <para> </para> </refsynopsisdiv> <refsection> <title>Description</title> <para> y = medfilt1(x) -Applies a 3rd order 1-dimensional median filter to input x along the -first non-zero dimension. The function appropriately pads the signal + </para> +<para>Applies a 3rd order 1-dimensional median filter to input x along the +first non-zero dimension.</para> + <para>The function appropriately pads the signal with zeros at the endings. For a segment, a median is calculated as the middle value (average of two middle values) for odd number -number (even number) of data points. -y = medfilt1(x,n) -Applies a nth order 1-dimensional median filter. -y = medfilt1(x,n,dim) -Applies the median filter along the n-th dimension -y = medfilt1(__, nanflag, padding) -nanflag specifies how NaN values are treated. padding specifies the -type of filtering to be performed at the signal edges. - </para> - <para> -</para> +number (even number) of data points.</para> +<para> </para> +<para>y = medfilt1(x,n)</para> +<para>Applies a nth order 1-dimensional median filter.</para> +<para> </para> +<para>y = medfilt1(x,n,dim)</para> +<para>Applies the median filter along the n-th dimension</para> +<para> </para> +<para>y = medfilt1(__, nanflag, padding)</para> +<para>nanflag specifies how NaN values are treated. padding specifies the +type of filtering to be performed at the signal edges.</para> + + <para> </para> </refsection> <refsection> <title>Parameters</title> <variablelist> <varlistentry><term>x:</term> - <listitem><para> int | double</para></listitem></varlistentry> + <listitem><para> int | double</para> <para>Input signal.</para></listitem></varlistentry> <varlistentry><term>n:</term> - <listitem><para> positive integer scalar</para></listitem></varlistentry> + <listitem><para> positive integer, scalar</para><para> + Filter order. </para> + <para> Defaults to 3.The order of the median filter. Must be less than + (length of the signal) where signals are 1D vectors along the + dimension of x to be filtered </para></listitem></varlistentry> <varlistentry><term>dim:</term> - <listitem><para> positive integer scalar</para></listitem></varlistentry> + <listitem><para> positive integer scalar</para><para> + Dimension to filter along. </para> + <para> Defaults to first non-singleton dimension of x</para></listitem></varlistentry> <varlistentry><term>nanflag:</term> - <listitem><para> 'includenan' (default) | 'omitnan'</para></listitem></varlistentry> - <varlistentry><term>* includenan:</term> - <listitem><para> Filtering such that the median of any segment</para></listitem></varlistentry> - <varlistentry><term>* omitnan:</term> - <listitem><para> Filtering with NaNs omitted in each segment. If a segment</para></listitem></varlistentry> + <listitem><para> 'includenan' (default) | 'omitnan'</para> <para> + NaN condition.</para> + <para> * includenan: Filtering such that the median of any segment containing a NaN is also a NaN. </para> + <para>* omitnan: Filtering with NaNs omitted in each segment. If a segment contains all NaNs, the result is NaN</para> +</listitem></varlistentry> + <varlistentry><term>y:</term> - <listitem><para> int | double</para></listitem></varlistentry> + <listitem><para> int | double</para><para> + The filtered signal.</para> + <para>y has the same size as x</para></listitem></varlistentry> </variablelist> + <para> </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -1) Noise supression using median filtering -fs = 1e3; -t = 1:1/fs:1; -s = sin(2*%pi*2*t)+ cos(2*%pi*5*t); -// Adding noise -x = s + 0.1*randn(size(s)); -y = medfilt1(x); +//Generate a sinusoidal signal sampled for 1 second at 100 Hz. Add a higher-frequency sinusoid to simulate noise. +fs = 100; +t = 0:1/fs:1; +x = sin(2*%pi*t*3)+0.25*sin(2*%pi*t*40); +//Use a 10th-order median filter to smooth the signal. Plot the result. +y = medfilt1(x,10); +plot(t,x,t,y) +legend('Original','Filtered'); +y = round(y*10000)/10000; +y = y' ]]></programlisting> + +<scilab:image> +//Generate a sinusoidal signal sampled for 1 second at 100 Hz. Add a higher-frequency sinusoid to simulate noise. +fs = 100; +t = 0:1/fs:1; +x = sin(2*%pi*t*3)+0.25*sin(2*%pi*t*40); + +//Use a 10th-order median filter to smooth the signal. Plot the result. +y = medfilt1(x,10); +plot(t,x,t,y) +legend('Original','Filtered'); +y = round(y*10000)/10000; +y = y' +</scilab:image> + + </refsection> <refsection> diff --git a/help/en_US/movingrms.xml b/help/en_US/movingrms.xml index c40672d..5498eb9 100644 --- a/help/en_US/movingrms.xml +++ b/help/en_US/movingrms.xml @@ -17,52 +17,54 @@ <refnamediv> <refname>movingrms</refname> - <refpurpose></refpurpose> + <refpurpose>Find moving RMS value of signal in x</refpurpose> + <para> </para> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - [rmsx,w]=movingrms(x,w,rc,Fs=1) + [rmsx,w]=movingrms(x,width,risetime) + [rmsx,w]=movingrms(x,width,risetime,Fs) </synopsis> + <para> </para> </refsynopsisdiv> <refsection> <title>Parameters</title> <variablelist> <varlistentry><term>x:</term> - <listitem><para> Real or complex valued vector or matrix</para></listitem></varlistentry> - <varlistentry><term>w:</term> + <listitem><para> (Real or complex valued vector or matrix) Input signal samples</para></listitem></varlistentry> + <varlistentry><term>width:</term> <listitem><para> Real or complex scalar value</para></listitem></varlistentry> - <varlistentry><term>rc:</term> + <varlistentry><term>risetime:</term> <listitem><para> Real or complex scalar value</para></listitem></varlistentry> <varlistentry><term>Fs:</term> - <listitem><para> Real or complex scalar value</para></listitem></varlistentry> + <listitem><para> (Real or complex scalar value) Smapling frequency</para></listitem></varlistentry> </variablelist> + <para> </para> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -The signal is convoluted against a sigmoid window of width w and risetime rc with the units of these parameters relative to the value of the sampling frequency given in Fs (Default value=1). +In this function signal is convoluted against a sigmoid window of width w and risetime rc with the units of these parameters relative to the value of the sampling frequency given in Fs (Default value=1). </para> + <para> </para> </refsection> <refsection> - <title>Examples</title> + <title>Example : 1</title> + <programlisting role="example"><![CDATA[ +[a,b]=movingrms ([4.4 94 1;-2 5*%i 5],1,-2) // moving rms with default value of Fs = 1 + ]]></programlisting> + +<title>Example : 2</title> <programlisting role="example"><![CDATA[ -1. [a,b]=movingrms ([4.4 94 1;-2 5i 5],1,-2) -a = 0.91237 17.71929 0.96254 -0.91237 17.71929 0.96254 -b = 0.18877 -0.18877 -2. [a,b]=movingrms ([4.4 94 1;-2 5i 5],1,-2,2) -a = 4.8332 93.8669 5.0990 -4.8332 93.8669 5.0990 -b = 1 -1 +[a,b]=movingrms ([4.4 94 1;-2 5*%i 5],1,-2,2)// moving rms with value of Fs = 2 + ]]></programlisting> </refsection> + </refentry> diff --git a/help/en_US/ncauer.xml b/help/en_US/ncauer.xml index a9395af..3260e0f 100644 --- a/help/en_US/ncauer.xml +++ b/help/en_US/ncauer.xml @@ -25,8 +25,6 @@ <title>Calling Sequence</title> <synopsis> [Zz, Zp, Zg] = ncauer(Rp, Rs, n) - [Zz, Zp] = ncauer(Rp, Rs, n) - Zz = ncauer(Rp, Rs, n) </synopsis> </refsynopsisdiv> @@ -36,36 +34,45 @@ <varlistentry><term>n:</term> <listitem><para> Filter Order</para></listitem></varlistentry> <varlistentry><term>Rp:</term> - <listitem><para> Peak-to-peak passband ripple</para></listitem></varlistentry> + <listitem><para> Peak-to-peak passband ripple in dB</para></listitem></varlistentry> <varlistentry><term>Rs:</term> - <listitem><para> Stopband attenuation</para></listitem></varlistentry> + <listitem><para> Stopband attenuation in dB</para></listitem></varlistentry> + <varlistentry><term>Zz:</term> + <listitem><para> Zeros</para></listitem></varlistentry> + <varlistentry><term>Zp:</term> + <listitem><para> Poles</para></listitem></varlistentry> + <varlistentry><term>Zg:</term> + <listitem><para> Gain</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -It designs an analog prototype for Cauer filter of nth order, with a Peak-to-peak passband ripple of Rp and a stopband attenuation of Rs. +It gives an analog prototype for Cauer filter (elliptic filter) of nth order, with a Peak-to-peak passband ripple of Rp and a stopband attenuation of Rs. </para> +<para> +This function is same as ellipap() only order of input argument is different,</para> + <para> This function is only for octave compatibility only </para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -n = 5; -Rp = 5; -Rs = 5; +n = 4; +Rp = 3; +Rs = 10; [Zz, Zp, Zg] = ncauer(Rp, Rs, n) -Zz = -0.0000 + 2.5546i 0.0000 + 1.6835i -0.0000 - 2.5546i -0.0000 - 1.6835i - -Zp = - --0.10199 + 0.64039i -0.03168 + 0.96777i -0.10199 - 0.64039i -0.03168 - 0.96777i -0.14368 + 0.00000i - -Zg = 0.0030628 ]]></programlisting> </refsection> + + <refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Sonu Sharma, RGIT Mumbai</member> + <member>FOSSEE, IIT Bombay</member> + </simplelist> + </refsection> + </refentry> diff --git a/help/en_US/postpad.xml b/help/en_US/postpad.xml new file mode 100644 index 0000000..8c96bae --- /dev/null +++ b/help/en_US/postpad.xml @@ -0,0 +1,74 @@ +<?xml version="1.0" encoding="UTF-8"?> + +<!-- + * + * This help file was generated from postpad.sci using help_from_sci(). + * + --> + +<refentry version="5.0-subset Scilab" xml:id="postpad" xml:lang="en" + xmlns="http://docbook.org/ns/docbook" + xmlns:xlink="http://www.w3.org/1999/xlink" + xmlns:svg="http://www.w3.org/2000/svg" + xmlns:ns3="http://www.w3.org/1999/xhtml" + xmlns:mml="http://www.w3.org/1998/Math/MathML" + xmlns:scilab="http://www.scilab.org" + xmlns:db="http://docbook.org/ns/docbook"> + + <refnamediv> + <refname>postpad</refname> + <refpurpose></refpurpose> + </refnamediv> + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> + Y = postpad (X, L) + Y = postpad (X, L, C) + </synopsis> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>X:</term> + <listitem><para>Input vector or matrix of real numbers.</para></listitem></varlistentry> + <varlistentry><term>L:</term> + <listitem><para> The length of the final postpadded sequence.</para></listitem></varlistentry> + <varlistentry><term>C:</term> + <listitem><para>number used for postpadding.</para></listitem></varlistentry> + <varlistentry><term>Y:</term> + <listitem><para>Output</para></listitem></varlistentry> + </variablelist> +</refsection> + +<refsection> + <title>Description</title> + <para> + Append the scalar value C to the vector X until it is of length L. + </para> + <para> + If C is not given, a value of 0 is used. + </para> + <para> + If 'length (X) > L', elements from the end of X are removed until a vector of length L is obtained. + </para> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ + x = [1 2 3]; + L = 6; + y = postpad(x, L) + ]]></programlisting> +</refsection> + + <refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> + </refsection> + +</refentry> diff --git a/help/en_US/pulseperiod.xml b/help/en_US/pulseperiod.xml index 7fc379f..c28e26e 100644 --- a/help/en_US/pulseperiod.xml +++ b/help/en_US/pulseperiod.xml @@ -17,20 +17,86 @@ <refnamediv> <refname>pulseperiod</refname> - <refpurpose></refpurpose> + <refpurpose>This function estimate pulse period of real vector x.</refpurpose> + <para> </para> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - p=pulseperiod(x) - p=pulseperiod(x, Fs) - p=pulseperiod(x, t) - p=pulseperiod (x, t, 'Polarity', pol) - p=pulseperiod(x, t, 'MidPercentReferenceLevel', N ) - p=pulseperiod(x, t, 'Tolerance', M) - p=pulseperiod(x, t,'StateLevels', O) + p=pulseperiod(x) + p=pulseperiod(x, Fs) + p=pulseperiod(x, t) + p=pulseperiod (x, t, 'Polarity', pol) + p=pulseperiod(x, t, 'MidPercentReferenceLevel', N ) + p=pulseperiod(x, t, 'Tolerance', M) + p=pulseperiod(x, t,'StateLevels', O) + [p initialcross finalcross nextcross midreference]=pulseperiod(x) + [p initialcross finalcross nextcross midreference]=pulseperiod(x, t) + [p initialcross finalcross nextcross midreference]=pulseperiod(x, t) + [p initialcross finalcross nextcross midreference]=pulseperiod(x, t, 'Polarity', pol) + [p initialcross finalcross nextcross midreference]=pulseperiod(x, t, 'MidPercentReferenceLevel', N ) + [p initialcross finalcross nextcross midreference]= pulseperiod(x, t, 'Tolerance', M) + [p initialcross finalcross nextcross midreference]= pulseperiod(x, t,'StateLevels', O) + [p initialcross finalcross nextcross midreference]= pulseperiod(x, t,'StateLevels', O, 'fig', f) </synopsis> + <para> </para> </refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>x</term> + <listitem><para> : real input vector </para></listitem></varlistentry> + <varlistentry><term>Fs</term> + <listitem><para> : specifies the sample rate, Fs, as a positive scalar, where the first sample instant corresponds to a time of zero. </para></listitem></varlistentry> + <varlistentry><term>t</term> + <listitem><para> : defiene instant sample time t as vector with same length of x, or specifies the sample rate, t, as a positive scalar.</para></listitem></varlistentry> + <varlistentry><term> 'Polarity', pol</term> + <listitem><para> : pol specify the polarity of the pulse as either 'positive' or 'negative', where the default value is 'positive'</para></listitem></varlistentry> + <varlistentry><term> 'MidPercentReferenceLevel', N </term> + <listitem><para> : specify the mid percent reference leves as a percentage, default value of N is 50.</para></listitem></varlistentry> + <varlistentry><term> 'Tolerance', M </term> + <listitem><para> : define the tolerance value as real scaler value, where default value of M is 2.0.</para></listitem></varlistentry> + <varlistentry><term>'StateLevels', O</term> + <listitem><para> : O define the lower and upper state levels as two element real vector.</para></listitem></varlistentry> + <varlistentry><term> 'fig', f</term> + <listitem><para> : f specify the logical input value to display figure as one of 'on' or 'off', where the default input in 'off'.</para></listitem></varlistentry> + + <varlistentry><term> p </term> + <listitem><para> : returns a vector of difference between the mid-crossings of the initial transition of each positive-polarity pulse and the next positive-going transition </para></listitem></varlistentry> + <varlistentry><term> initialcross </term> + <listitem><para> : returns a vector of initial cross values of bilevel waveform transitions x.</para></listitem></varlistentry> + <varlistentry><term> finalcross </term> + <listitem><para> : returns a vector of final cross values of bilevel waveform transitions x.</para></listitem></varlistentry> + <varlistentry><term> nextcross </term> + <listitem><para> : returns a vector of next cross values of bilevel waveform transitions x. </para></listitem></varlistentry> + <varlistentry><term> midreference </term> + <listitem><para> : return mid reference value corrosponding to mid percent reference value. </para></listitem></varlistentry> +</variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Examples </title> + + <programlisting role="example"><![CDATA[ + + x = fscanfMat("macros/pulsedata_x.txt"); //Importing samples of pulse + t = fscanfMat("macros/pulsedata_t.txt"); + clf //clearing plot history + p = pulseperiod(x,t,'fig','ON') // Detremining pulse period and ploting it + +]]></programlisting> + +<scilab:image> + x = [0. 0.0108 0.0367 -0.0452 0.0172 0.0064 -0.0262 -0.0087 0.0069 0.0716 0.0554 -0.027 0.0607 5.0145 4.9987 5.0143 4.9959 4.9975 5.0298 0.0282 0.0283 0.0134 -0.0241 0.0143 0.0326 0.0098 0.0207 0.0145 -0.0061 0.0059 -0.0157 0.0178 -0.0229 4.9786]; + t = [0. 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.225 0.25 0.275 0.3 0.325 0.35 0.375 0.4 0.425 0.45 0.475 0.5 0.525 0.55 0.575 0.6 0.625 0.65 0.675 0.7 0.725 0.75 0.775 0.8 0.825 ]; + clf + p = pulseperiod(x,t,'fig','ON') +</scilab:image> + +</refsection> + </refentry> diff --git a/help/en_US/pulsesep.xml b/help/en_US/pulsesep.xml index 4c28fd4..32a8915 100644 --- a/help/en_US/pulsesep.xml +++ b/help/en_US/pulsesep.xml @@ -17,20 +17,86 @@ <refnamediv> <refname>pulsesep</refname> - <refpurpose></refpurpose> + <refpurpose>This function estimate pulse separation between bilevel waveform pulses.</refpurpose> + <para> </para> </refnamediv> <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - s=pulsesep(x) - s=pulsesep(x, Fs) - s=pulsesep(x, t) - s=pulsesep (x, t, 'Polarity', pol) - s=pulsesep(x, t, 'MidPercentReferenceLevel', N ) - s=pulsesep(x, t, 'Tolerance', M) - s=pulsesep(x, t,'StateLevels', [O 1]) + s=pulsesep(x) + s=pulsesep(x, Fs) + s=pulsesep(x, t) + s=pulsesep (x, t, 'Polarity', pol) + s=pulsesep(x, t, 'MidPercentReferenceLevel', N ) + s=pulsesep(x, t, 'Tolerance', M) + s=pulsesep(x, t,'StateLevels', O) + [s initialcross finalcross nextcross midreference]=pulsesep(x) + [s initialcross finalcross nextcross midreference]=pulsesep(x, t) + [s initialcross finalcross nextcross midreference]=pulsesep(x, t) + [s initialcross finalcross nextcross midreference]=pulsesep(x, t, 'Polarity', pol) + [s initialcross finalcross nextcross midreference]=pulsesep(x, t, 'MidPercentReferenceLevel', N ) + [s initialcross finalcross nextcross midreference]= pulsesep(x, t, 'Tolerance', M) + [s initialcross finalcross nextcross midreference]= pulsesep(x, t,'StateLevels', O) + [s initialcross finalcross nextcross midreference]= pulsesep(x, t,'StateLevels', O, 'fig', f) </synopsis> + <para> </para> </refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>x</term> + <listitem><para> : real input vector </para></listitem></varlistentry> + <varlistentry><term>Fs</term> + <listitem><para> : specifies the sample rate, Fs, as a positive scalar, where the first sample instant corresponds to a time of zero. </para></listitem></varlistentry> + <varlistentry><term>t</term> + <listitem><para> : defiene instant sample time t as vector with same length of x, or specifies the sample rate, t, as a positive scalar.</para></listitem></varlistentry> + <varlistentry><term> 'Polarity', pol</term> + <listitem><para> : pol specify the polarity of the pulse as either 'positive' or 'negative', where the default value is 'positive'</para></listitem></varlistentry> + <varlistentry><term> 'MidPercentReferenceLevel', N </term> + <listitem><para> : specify the mid percent reference leves as a percentage, default value of N is 50.</para></listitem></varlistentry> + <varlistentry><term> 'Tolerance', M </term> + <listitem><para> : define the tolerance value as real scaler value, where default value of M is 2.0.</para></listitem></varlistentry> + <varlistentry><term>'StateLevels', O</term> + <listitem><para> : O define the lower and upper state levels as two element real vector.</para></listitem></varlistentry> + <varlistentry><term> 'fig', f</term> + <listitem><para> : f specify the logical input value to display figure as one of 'on' or 'off', where the default input in 'off'.</para></listitem></varlistentry> + + <varlistentry><term> s </term> + <listitem><para> : returns a vector of differences between the mid-crossings of each final negative-going transition of every positive-polarity pulse and the next positive-going transition. </para></listitem></varlistentry> + <varlistentry><term> initialcross </term> + <listitem><para> : returns a vector of initial cross values of bilevel waveform transitions x.</para></listitem></varlistentry> + <varlistentry><term> finalcross </term> + <listitem><para> : returns a vector of final cross values of bilevel waveform transitions x.</para></listitem></varlistentry> + <varlistentry><term> nextcross </term> + <listitem><para> : returns a vector of next cross values of bilevel waveform transitions x. </para></listitem></varlistentry> + <varlistentry><term> midreference </term> + <listitem><para> : return mid reference value corrosponding to mid percent reference value. </para></listitem></varlistentry> +</variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Examples </title> + + <programlisting role="example"><![CDATA[ + + x = fscanfMat("macros/pulsedata_x.txt"); //Importing samples of pulse + t = fscanfMat("macros/pulsedata_t.txt"); + clf //clearing plot history + p = pulsesep(x,t,'fig','ON') // Detremining pulse separation and ploting it + +]]></programlisting> + +<scilab:image> + x = [0. 0.0108 0.0367 -0.0452 0.0172 0.0064 -0.0262 -0.0087 0.0069 0.0716 0.0554 -0.027 0.0607 5.0145 4.9987 5.0143 4.9959 4.9975 5.0298 0.0282 0.0283 0.0134 -0.0241 0.0143 0.0326 0.0098 0.0207 0.0145 -0.0061 0.0059 -0.0157 0.0178 -0.0229 4.9786]; + t = [0. 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.225 0.25 0.275 0.3 0.325 0.35 0.375 0.4 0.425 0.45 0.475 0.5 0.525 0.55 0.575 0.6 0.625 0.65 0.675 0.7 0.725 0.75 0.775 0.8 0.825 ]; + clf + p = pulsesep(x,t,'fig','ON') +</scilab:image> + +</refsection> + </refentry> diff --git a/help/en_US/pulsewidth.xml b/help/en_US/pulsewidth.xml index ee08682..9964429 100644 --- a/help/en_US/pulsewidth.xml +++ b/help/en_US/pulsewidth.xml @@ -17,20 +17,85 @@ <refnamediv> <refname>pulsewidth</refname> - <refpurpose></refpurpose> + <refpurpose>This function estimate pulse width of real vector x.</refpurpose> + <para> </para> </refnamediv> - <refsynopsisdiv> <title>Calling Sequence</title> <synopsis> - w=pulsewidth(x) - w=pulsewidth(x, Fs) - w=pulsewidth(x, t) - w=pulsewidth (x, t, 'Polarity', pol) - w=pulsewidth(x, t, 'MidPercentReferenceLevel', N ) - w=pulsewidth(x, t, 'Tolerance', M) - w=pulsewidth(x, t,'StateLevels', O) + p=pulsewidth(x) + p=pulsewidth(x, Fs) + p=pulsewidth(x, t) + p=pulsewidth (x, t, 'Polarity', pol) + p=pulsewidth(x, t, 'MidPercentReferenceLevel', N ) + p=pulsewidth(x, t, 'Tolerance', M) + p=pulsewidth(x, t,'StateLevels', O) + [p initialcross finalcross nextcross midreference]=pulsewidth(x) + [p initialcross finalcross nextcross midreference]=pulsewidth(x, t) + [p initialcross finalcross nextcross midreference]=pulsewidth(x, t) + [p initialcross finalcross nextcross midreference]=pulsewidth(x, t, 'Polarity', pol) + [p initialcross finalcross nextcross midreference]=pulsewidth(x, t, 'MidPercentReferenceLevel', N ) + [p initialcross finalcross nextcross midreference]= pulsewidth(x, t, 'Tolerance', M) + [p initialcross finalcross nextcross midreference]= pulsewidth(x, t,'StateLevels', O) + [p initialcross finalcross nextcross midreference]= pulsewidth(x, t,'StateLevels', O, 'fig', f) </synopsis> + <para> </para> </refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>x</term> + <listitem><para> : real input vector </para></listitem></varlistentry> + <varlistentry><term>Fs</term> + <listitem><para> : specifies the sample rate, Fs, as a positive scalar, where the first sample instant corresponds to a time of zero. </para></listitem></varlistentry> + <varlistentry><term>t</term> + <listitem><para> : defiene instant sample time t as vector with same length of x, or specifies the sample rate, t, as a positive scalar.</para></listitem></varlistentry> + <varlistentry><term> 'Polarity', pol</term> + <listitem><para> : pol specify the polarity of the pulse as either 'positive' or 'negative', where the default value is 'positive'</para></listitem></varlistentry> + <varlistentry><term> 'MidPercentReferenceLevel', N </term> + <listitem><para> : specify the mid percent reference leves as a percentage, default value of N is 50.</para></listitem></varlistentry> + <varlistentry><term> 'Tolerance', M </term> + <listitem><para> : define the tolerance value as real scaler value, where default value of M is 2.0.</para></listitem></varlistentry> + <varlistentry><term>'StateLevels', O</term> + <listitem><para> : O define the lower and upper state levels as two element real vector.</para></listitem></varlistentry> + <varlistentry><term> 'fig', f</term> + <listitem><para> : f specify the logical input value to display figure as one of 'on' or 'off', where the default input in 'off'.</para></listitem></varlistentry> + + <varlistentry><term> p </term> + <listitem><para> : returns a vector of difference between the mid-crossings of the initial transition of each positive-polarity pulse and the next positive-going transition </para></listitem></varlistentry> + <varlistentry><term> initialcross </term> + <listitem><para> : returns a vector of initial cross values of bilevel waveform transitions x.</para></listitem></varlistentry> + <varlistentry><term> finalcross </term> + <listitem><para> : returns a vector of final cross values of bilevel waveform transitions x.</para></listitem></varlistentry> + <varlistentry><term> nextcross </term> + <listitem><para> : returns a vector of next cross values of bilevel waveform transitions x. </para></listitem></varlistentry> + <varlistentry><term> midreference </term> + <listitem><para> : return mid reference value corrosponding to mid percent reference value. </para></listitem></varlistentry> +</variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Examples </title> + + <programlisting role="example"><![CDATA[ + + x = fscanfMat("macros/pulsedata_x.txt"); //Importing samples of pulse + t = fscanfMat("macros/pulsedata_t.txt"); + clf //clearing plot history + p = pulsewidth(x,t,'fig','ON') // Detremining pulse width and ploting it + +]]></programlisting> + +<scilab:image> + x = [0. 0.0108 0.0367 -0.0452 0.0172 0.0064 -0.0262 -0.0087 0.0069 0.0716 0.0554 -0.027 0.0607 5.0145 4.9987 5.0143 4.9959 4.9975 5.0298 0.0282 0.0283 0.0134 -0.0241 0.0143 0.0326 0.0098 0.0207 0.0145 -0.0061 0.0059 -0.0157 0.0178 -0.0229 4.9786]; + t = [0. 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.225 0.25 0.275 0.3 0.325 0.35 0.375 0.4 0.425 0.45 0.475 0.5 0.525 0.55 0.575 0.6 0.625 0.65 0.675 0.7 0.725 0.75 0.775 0.8 0.825 ]; + clf + p = pulsewidth(x,t,'fig','ON') +</scilab:image> + +</refsection> + </refentry> diff --git a/help/en_US/sftrans.xml b/help/en_US/sftrans.xml index 56aee48..3a2e0c5 100644 --- a/help/en_US/sftrans.xml +++ b/help/en_US/sftrans.xml @@ -17,7 +17,7 @@ <refnamediv> <refname>sftrans</refname> - <refpurpose>Transform band edges of a generic lowpass filter (cutoff at W=1) represented in splane zero-pole-gain form.</refpurpose> + <refpurpose>Transform band edges of a prototype filter (cutoff at W=1) represented in s-plane zero-pole-gain form (Frequency Transformation in Analog domain).</refpurpose> </refnamediv> @@ -42,59 +42,39 @@ <varlistentry><term>W:</term> <listitem><para> Edge of target filter.</para></listitem></varlistentry> <varlistentry><term>stop:</term> - <listitem><para> True for high pass and band stop filters or false for low pass and band pass filters.</para></listitem></varlistentry> + <listitem><para> True(%T or 1) for high pass and band stop filters or false (%F or 0) for low pass and band pass filters.</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -Theory: Given a low pass filter represented by poles and zeros in the splane, you can convert it to a low pass, high pass, band pass or band stop by transforming each of the poles and zeros -individually. The following table summarizes the transformation: - </para> - <para> -Transform Zero at x Pole at x ----------------- ------------------------- ------------------------ -Low Pass zero: Fc x/C pole: Fc x/C -S -> C S/Fc gain: C/Fc gain: Fc/C ----------------- ------------------------- ------------------------ -High Pass zero: Fc C/x pole: Fc C/x -S -> C Fc/S pole: 0 zero: 0 -gain: -x gain: -1/x ----------------- ------------------------- ------------------------ -Band Pass zero: b +- sqrt(b^2-FhFl) pole: b +- sqrt(b^2-FhFl) -S^2+FhFl pole: 0 zero: 0 -S -> C -------- gain: C/(Fh-Fl) gain: (Fh-Fl)/C -S(Fh-Fl) b=x/C (Fh-Fl)/2 b=x/C (Fh-Fl)/2 ----------------- ------------------------- ------------------------ -Band Stop zero: b +- sqrt(b^2-FhFl) pole: b +- sqrt(b^2-FhFl) -S(Fh-Fl) pole: +-sqrt(-FhFl) zero: +-sqrt(-FhFl) -S -> C -------- gain: -x gain: -1/x -S^2+FhFl b=C/x (Fh-Fl)/2 b=C/x (Fh-Fl)/2 ----------------- ------------------------- ------------------------ -Bilinear zero: (2+xT)/(2-xT) pole: (2+xT)/(2-xT) -2 z-1 pole: -1 zero: -1 -S -> - --- gain: (2-xT)/T gain: (2-xT)/T -T z+1 ----------------- ------------------------- ------------------------ - </para> - <para> -where C is the cutoff frequency of the initial lowpass filter, Fc is the edge of the target low/high pass filter and [Fl,Fh] are the edges of the target band pass/stop filter. With abundant tedious -algebra, you can derive the above formulae yourself by substituting the transform for S into H(S)=S-x for a zero at x or H(S)=1/(S-x) for a pole at x, and converting the result into the form: - </para> - <para> -H(S)=g prod(S-Xi)/prod(S-Xj) -</para> +Given a low pass filter represented by poles and zeros in the splane, can be converted into a </para> +<para> low pass (having diffrent cutoff frequency),</para> +<para> high pass,</para> +<para> band pass,</para> +<para> band stop.</para> +<para> by transforming each of the poles and zeros individually.</para> </refsection> <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -[Sz, Sp, Sg] = sftrans (5, 10, 15, 20, 30) -Sz = 4 -Sp = 2 -Sg = 7.5000 +Sz = [1 2 3]; +Sp = [4 5 6]; +Sg = 15; +W = 20; +stop = %T; +[Sz, Sp, Sg] = sftrans (Sz, Sp, Sg, W, stop) + ]]></programlisting> </refsection> + +<refsection> +<title>Modified by :</title> +<simplelist type="vert"> +<member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> +</refsection> + </refentry> diff --git a/help/en_US/sigmoid_train.xml b/help/en_US/sigmoid_train.xml index 6f57b3f..3e23d09 100644 --- a/help/en_US/sigmoid_train.xml +++ b/help/en_US/sigmoid_train.xml @@ -17,7 +17,8 @@ <refnamediv> <refname>sigmoid_train</refname> - <refpurpose>Evaluate a train of sigmoid functions at T.</refpurpose> + <refpurpose>Evaluate a train of sigmoid functions at t.</refpurpose> + <para> </para> </refnamediv> @@ -35,6 +36,8 @@ <listitem><para> integer</para></listitem></varlistentry> <varlistentry><term>ranges:</term> <listitem><para> matrix</para></listitem></varlistentry> + <varlistentry><term>rc:</term> + <listitem><para> time constant (scalar)</para></listitem></varlistentry> </variablelist> </refsection> @@ -49,8 +52,6 @@ The number and duration of each sigmoid is determined from RANGES. Each row of R <title>Examples</title> <programlisting role="example"><![CDATA[ sigmoid_train(0.1,[1:3],4) -ans = -0.27375 ]]></programlisting> </refsection> </refentry> diff --git a/help/en_US/stmcb.xml b/help/en_US/stmcb.xml index 2490a4b..7972926 100644 --- a/help/en_US/stmcb.xml +++ b/help/en_US/stmcb.xml @@ -17,7 +17,128 @@ <refnamediv> <refname>stmcb</refname> - <refpurpose>function [b,a] = stmcb( x, u_in, q, p, niter, a_in )</refpurpose> + <refpurpose>Compute linear model using Steiglitz-McBride iteration</refpurpose> + <para> </para> </refnamediv> + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> +[b,a] = stmcb(h,nb,na) +[b,a] = stmcb(y,x,nb,na) +[b,a] = stmcb(h,nb,na,niter) +[b,a] = stmcb(y,x,nb,na,niter) +[b,a] = stmcb(h,nb,na,niter,ai) +[b,a] = stmcb(y,x,nb,na,niter,ai) + </synopsis> + <para> </para> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>b,a </term> + <listitem><para> : coefficients of the system function,nb is number of zeros and na is number of poles</para></listitem></varlistentry> + <varlistentry><term>h</term> + <listitem><para> : impulse response of the system</para></listitem></varlistentry> + <varlistentry><term>x, y</term> + <listitem><para> : input and output of same length given to the system</para></listitem></varlistentry> + <varlistentry><term>nitren</term> + <listitem><para> : number of iterations</para></listitem></varlistentry> + <varlistentry><term>ai</term> + <listitem><para> : initial estimate of the denominator coefficients</para></listitem></varlistentry> + <para> </para> + <para>Accepts only real i/ps, complex i/ps are not accepted due to limitations of the 'filter' function in Scilab</para> +</variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +h = fscanfMat("macros/stmcb_h_data.txt"); //required impulse response samples +plot(h); //plotting required impulse response +title "Required impulse respose (h) plot " +xlabel "samples (n)" +ylabel "magnitude {h(n)} " +nb = 4 ; // four zeros +na = 4 ; //four poles +stmcb(h,nb,na) + ]]></programlisting> + +<scilab:image> +h = [0.0003 +0.0033 +0.0149 +0.0432 +0.0911 +0.1493 +0.1985 +0.2190 +0.2007 +0.1479 +0.0764 +0.0070 +-0.0429 +-0.0649 +-0.0601 +-0.0375 +-0.0092 +0.0142 +0.0265 +0.0267 +0.0180 +0.0057 +-0.0052 +-0.0115 +-0.0123 +-0.0088 +-0.0033 +0.0018 +0.0050 +0.0057 +0.0043 +0.0018 +-0.0006 +-0.0021 +-0.0026 +-0.0021 +-0.0010 +0.0001 +0.0009 +0.0012 +0.0010 +0.0005 +0.0000 +-0.0004 +-0.0005 +-0.0005 +-0.0003 +-0.0000 +0.0002 +0.0002 +0.0002 +0.0001 +0.0000 +-0.0001 +-0.0001 +-0.0001 +-0.0001 +-0.0000 +0.0000 +0.0000 +0.0000 +0.0000 +0.0000 +-0.0000 ] + +plot(h); //plotting required impulse response +title "Required impulse respose (h) plot " +xlabel "samples (n)" +ylabel "magnitude {h(n)} " + +</scilab:image> +</refsection> + </refentry> diff --git a/help/en_US/tf2zp.xml b/help/en_US/tf2zp.xml index 176e203..d8ae69b 100644 --- a/help/en_US/tf2zp.xml +++ b/help/en_US/tf2zp.xml @@ -17,7 +17,56 @@ <refnamediv> <refname>tf2zp</refname> - <refpurpose>[z,p,k]= tf2zp(b,a);</refpurpose> + <refpurpose>Transfer function to zero pole conversion</refpurpose> </refnamediv> +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> + [z p k] = tf2zp(num, den) + </synopsis> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>z:</term> + <listitem><para> Zeros</para></listitem></varlistentry> + <varlistentry><term>p:</term> + <listitem><para> Poles</para></listitem></varlistentry> + <varlistentry><term>k:</term> + <listitem><para> Leading coefficient (Gain)</para></listitem></varlistentry> + <varlistentry><term>Num:</term> + <listitem><para> Numerator coefficients of the transfer function</para></listitem></varlistentry> + <varlistentry><term>den:</term> + <listitem><para> Denomenator coefficients of the transfer function</para></listitem></varlistentry> + </variablelist> +</refsection> + +<refsection> + <title>Description</title> + <para> +It converts transfer function representation to zeros / poles representation. +</para> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +b = [1 2 3] +a = [4 5 6] +[z, p, k] = zp2tf(b, a) + + ]]></programlisting> +</refsection> + + <refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Debdeep Dey (FOSSEE, IIT Bombay)</member> + <member>MODIFIED BY: Sonu Sharma (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> + </refsection> + + </refentry> diff --git a/help/en_US/wconv.xml b/help/en_US/wconv.xml index acbf777..4fe678b 100644 --- a/help/en_US/wconv.xml +++ b/help/en_US/wconv.xml @@ -33,20 +33,26 @@ <title>Parameters</title> <variablelist> <varlistentry><term>type:</term> - <listitem><para> convolution type.</para></listitem></varlistentry> + <listitem><para> convolution type.</para> + <para> * 1 or "1" for 1D convolution.</para> + <para> * 2 or "2" for 2D convolution.</para> + </listitem></varlistentry> <varlistentry><term>x:</term> <listitem><para> Signal vector or matrix.</para></listitem></varlistentry> <varlistentry><term>f:</term> <listitem><para> FIR filter coefficients.</para></listitem></varlistentry> <varlistentry><term>shape:</term> - <listitem><para> Shape.</para></listitem></varlistentry> + <listitem> + <para> * "full", computes the full one/two-dimensional convolution. It is the default value.</para> + <para> * "same", computes the central part of the convolution of the same size as x.</para> + <para> * "valid", computes the convolution parts without the zero-padding of x.</para> + </listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. It performs 1D or 2D convolution between the signal x and the filter coefficients f. </para> </refsection> @@ -54,11 +60,17 @@ It performs 1D or 2D convolution between the signal x and the filter coefficient <refsection> <title>Examples</title> <programlisting role="example"><![CDATA[ -a = [1 2 3 4 5] -b = [7 8 9 10] -wconv(1,a,b) -ans = -7 22 46 80 114 106 85 50 +a = [1 2 3 4 5]; +b = [7 8 9 10]; +wconv(1, a, b) ]]></programlisting> </refsection> + + <refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> + </refsection> + </refentry> diff --git a/help/en_US/xcorr1.xml b/help/en_US/xcorr1.xml deleted file mode 100644 index b89de1a..0000000 --- a/help/en_US/xcorr1.xml +++ /dev/null @@ -1,81 +0,0 @@ -<?xml version="1.0" encoding="UTF-8"?> - -<!-- - * - * This help file was generated from xcorr1.sci using help_from_sci(). - * - --> - -<refentry version="5.0-subset Scilab" xml:id="xcorr1" xml:lang="en" - xmlns="http://docbook.org/ns/docbook" - xmlns:xlink="http://www.w3.org/1999/xlink" - xmlns:svg="http://www.w3.org/2000/svg" - xmlns:ns3="http://www.w3.org/1999/xhtml" - xmlns:mml="http://www.w3.org/1998/Math/MathML" - xmlns:scilab="http://www.scilab.org" - xmlns:db="http://docbook.org/ns/docbook"> - - <refnamediv> - <refname>xcorr1</refname> - <refpurpose>Estimates the cross-correlation.</refpurpose> - </refnamediv> - - -<refsynopsisdiv> - <title>Calling Sequence</title> - <synopsis> - [R, lag] = xcorr1 (X, Y, maxlag, scale) - [R, lag] = xcorr1 (X, Y, maxlag) - [R, lag] = xcorr1 (X, Y) - </synopsis> -</refsynopsisdiv> - -<refsection> - <title>Parameters</title> - <variablelist> - <varlistentry><term>X:</term> - <listitem><para> [non-empty; real or complex; vector or matrix] data.</para></listitem></varlistentry> - <varlistentry><term>Y:</term> - <listitem><para> [real or complex vector] data.</para></listitem></varlistentry> - <varlistentry><term>maxlag:</term> - <listitem><para> [integer scalar] maximum correlation lag If omitted, the default value is N-1, where N is the greater of the lengths of X and Y or, if X is a matrix, the number of rows in X.</para></listitem></varlistentry> - <varlistentry><term>scale:</term> - <listitem><para> [character string] specifies the type of scaling applied to the correlation vector (or matrix). is one of:</para></listitem></varlistentry> - </variablelist> -</refsection> - -<refsection> - <title>Description</title> - <para> -This is an Octave function. -Estimate the cross correlation R_xy(k) of vector arguments X and Y or, if Y is omitted, estimate autocorrelation R_xx(k) of vector X, for a range of lags k specified by argument "maxlag". If X is a -matrix, each column of X is correlated with itself and every other column. - </para> - <para> -The cross-correlation estimate between vectors "x" and "y" (of length N) for lag "k" is given by - </para> - <para> -N -R_xy(k) = sum x_{i+k} conj(y_i), -i=1 - </para> - <para> -where data not provided (for example x(-1), y(N+1)) is zero. Note the definition of cross-correlation given above. To compute a cross-correlation consistent with the field of statistics, see xcov. -</para> -</refsection> - -<refsection> - <title>Examples</title> - <programlisting role="example"><![CDATA[ -[R, lag] = xcorr1 ( [5 5], [2 2], 2, 'biased' ) - -R = - -0 5 10 5 0 - -lag = - --2 -1 0 1 2 - ]]></programlisting> -</refsection> -</refentry> diff --git a/help/en_US/xcov1.xml b/help/en_US/xcov1.xml deleted file mode 100644 index 3872563..0000000 --- a/help/en_US/xcov1.xml +++ /dev/null @@ -1,64 +0,0 @@ -<?xml version="1.0" encoding="UTF-8"?> - -<!-- - * - * This help file was generated from xcov1.sci using help_from_sci(). - * - --> - -<refentry version="5.0-subset Scilab" xml:id="xcov1" xml:lang="en" - xmlns="http://docbook.org/ns/docbook" - xmlns:xlink="http://www.w3.org/1999/xlink" - xmlns:svg="http://www.w3.org/2000/svg" - xmlns:ns3="http://www.w3.org/1999/xhtml" - xmlns:mml="http://www.w3.org/1998/Math/MathML" - xmlns:scilab="http://www.scilab.org" - xmlns:db="http://docbook.org/ns/docbook"> - - <refnamediv> - <refname>xcov1</refname> - <refpurpose>Compute covariance at various lags [=correlation(x-mean(x),y-mean(y))].</refpurpose> - </refnamediv> - - -<refsynopsisdiv> - <title>Calling Sequence</title> - <synopsis> - [R, lag] = xcov (X) - ... = xcov (X, Y) - ... = xcov (..., maxlag) - ... = xcov (..., scale) - </synopsis> -</refsynopsisdiv> - -<refsection> - <title>Parameters</title> - <variablelist> - <varlistentry><term>X:</term> - <listitem><para> Input vector</para></listitem></varlistentry> - <varlistentry><term>Y:</term> - <listitem><para> if specified, compute cross-covariance between X and Y, otherwise compute autocovariance of X.</para></listitem></varlistentry> - <varlistentry><term>maxlag:</term> - <listitem><para> is specified, use lag range [-maxlag:maxlag], otherwise use range [-n+1:n-1].</para></listitem></varlistentry> - <varlistentry><term>scale:</term> - <listitem><para> </para></listitem></varlistentry> - <varlistentry><term>'biased':</term> - <listitem><para> for covariance=raw/N,</para></listitem></varlistentry> - <varlistentry><term>'unbiased':</term> - <listitem><para> for covariance=raw/(N-|lag|),</para></listitem></varlistentry> - <varlistentry><term>'coeff':</term> - <listitem><para> for covariance=raw/(covariance at lag 0),</para></listitem></varlistentry> - <varlistentry><term>'none':</term> - <listitem><para> for covariance=raw</para></listitem></varlistentry> - <varlistentry><term>'none':</term> - <listitem><para> is the default.</para></listitem></varlistentry> - </variablelist> -</refsection> - -<refsection> - <title>Description</title> - <para> -Compute covariance at various lags [=correlation(x-mean(x),y-mean(y))]. Returns the covariance for each lag in the range, plus an optional vector of lags. -</para> -</refsection> -</refentry> diff --git a/help/en_US/zp2tf.xml b/help/en_US/zp2tf.xml index c9e16af..7d8852b 100644 --- a/help/en_US/zp2tf.xml +++ b/help/en_US/zp2tf.xml @@ -37,19 +37,18 @@ <varlistentry><term>p:</term> <listitem><para> Poles</para></listitem></varlistentry> <varlistentry><term>k:</term> - <listitem><para> Leading coefficient</para></listitem></varlistentry> + <listitem><para> Leading coefficient (Gain)</para></listitem></varlistentry> <varlistentry><term>Num:</term> - <listitem><para> Numerator of the transfer function</para></listitem></varlistentry> + <listitem><para> Numerator coefficients of the transfer function</para></listitem></varlistentry> <varlistentry><term>den:</term> - <listitem><para> Denomenator of the transfer function</para></listitem></varlistentry> + <listitem><para> Denomenator coefficients of the transfer function</para></listitem></varlistentry> </variablelist> </refsection> <refsection> <title>Description</title> <para> -This is an Octave function. -It converts zeros / poles to a transfer function. +It converts zeros / poles representation to transfer function representation. </para> </refsection> @@ -60,13 +59,16 @@ z = [1 2 3] p = [4 5 6] k = 5 [num, den] = zp2tf (z, p, k) -num = -5 -30 55 -30 - -den = - -1 -15 74 -120 ]]></programlisting> </refsection> + + <refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Sonu Sharma, RGIT Mumbai (fellow at FOSSEE, IIT Bombay)</member> + </simplelist> + </refsection> + + </refentry> diff --git a/help/en_US/zplane.xml b/help/en_US/zplane.xml index 64a7172..57b9d40 100644 --- a/help/en_US/zplane.xml +++ b/help/en_US/zplane.xml @@ -17,7 +17,53 @@ <refnamediv> <refname>zplane</refname> - <refpurpose>funcprot(0);</refpurpose> + <refpurpose>Pole-Zero plot for Discrete time systems</refpurpose> + <para> </para> </refnamediv> + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> +zplane(z); +zplane(z,p); + </synopsis> + <para> </para> +</refsynopsisdiv> + +<refsection> + <title>Description</title> + <para> +This function gives pole zero plote of discrete time systems + </para> + <para> </para> +</refsection> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>z</term> + <listitem><para> : vector containing numerator coefficients</para></listitem></varlistentry> + <varlistentry><term>p</term> + <listitem><para> : vector containing denumerator coefficients</para></listitem></varlistentry> + </variablelist> + <para> </para> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +z = [1 2 3]; +p = [4 5 6]; +zplane(z,p); + ]]></programlisting> + +<scilab:image> +z = [1 2 3]; +p = [4 5 6]; +zplane(z,p); +</scilab:image> + +</refsection> + </refentry> |