From b1f5c3f8d6671b4331cef1dcebdf63b7a43a3a2b Mon Sep 17 00:00:00 2001
From: priyanka
Date: Wed, 24 Jun 2015 15:03:17 +0530
Subject: initial commit / add all books

---
 830/CH12/EX12.1.1/spectrum_of_signal.sce        | 27 +++++++++
 830/CH12/EX12.1.2/spectrum_using_DFT.sce        | 81 +++++++++++++++++++++++++
 830/CH12/EX12.5.1/Additive_Noise_Parameters.sce | 26 ++++++++
 3 files changed, 134 insertions(+)
 create mode 100755 830/CH12/EX12.1.1/spectrum_of_signal.sce
 create mode 100755 830/CH12/EX12.1.2/spectrum_using_DFT.sce
 create mode 100755 830/CH12/EX12.5.1/Additive_Noise_Parameters.sce

(limited to '830/CH12')

diff --git a/830/CH12/EX12.1.1/spectrum_of_signal.sce b/830/CH12/EX12.1.1/spectrum_of_signal.sce
new file mode 100755
index 000000000..32b8c187f
--- /dev/null
+++ b/830/CH12/EX12.1.1/spectrum_of_signal.sce
@@ -0,0 +1,27 @@
+//Graphical//
+//Example 12.1.1
+//Determination of spectrum of a signal
+//With maximum normalized frequency f = 0.1
+//using Rectangular window and Blackmann window
+clear;
+close;
+clc;
+N = 61;
+cfreq = [0.1 0];
+[wft,wfm,fr]=wfir('lp',N,cfreq,'re',0);
+wft;                // Time domain filter coefficients
+wfm;                // Frequency domain filter values
+fr;                 // Frequency sample points
+WFM_dB = 20*log10(wfm);//Frequency response in dB
+for n = 1:N
+ h_balckmann(n)=0.42-0.5*cos(2*%pi*n/(N-1))+0.08*cos(4*%pi*n/(N-1));
+end
+wft_blmn = wft'.*h_balckmann;
+wfm_blmn = frmag(wft_blmn,length(fr));
+WFM_blmn_dB =20*log10(wfm_blmn);
+subplot(2,1,1)
+plot2d(fr,WFM_dB)
+xtitle('Frequency Response of Rectangular window Filtered output M = 61','Frequency in cycles per samples  f','Energy density in dB')
+subplot(2,1,2)
+plot2d(fr,WFM_blmn_dB)
+xtitle('Frequency Response of Blackmann window Filtered output M = 61','Frequency in cycles per samples  f','Energy density in dB')
diff --git a/830/CH12/EX12.1.2/spectrum_using_DFT.sce b/830/CH12/EX12.1.2/spectrum_using_DFT.sce
new file mode 100755
index 000000000..506617bcb
--- /dev/null
+++ b/830/CH12/EX12.1.2/spectrum_using_DFT.sce
@@ -0,0 +1,81 @@
+//Graphical//
+//Example 12.1.2
+//Evaluating power spectrum of a discrete sequence
+//Using N-point DFT
+clear;
+clc;
+close;
+N =16;  //Number of samples in given sequence
+n =0:N-1;
+delta_f = [0.06,0.01];//frequency separation
+x1 = sin(2*%pi*0.315*n)+cos(2*%pi*(0.315+delta_f(1))*n);
+x2 = sin(2*%pi*0.315*n)+cos(2*%pi*(0.315+delta_f(2))*n);
+L = [8,16,32,128];
+k1 = 0:L(1)-1;
+k2 = 0:L(2)-1;
+k3 = 0:L(3)-1;
+k4 = 0:L(4)-1;
+fk1 = k1./L(1);
+fk2 = k2./L(2);
+fk3 = k3./L(3);
+fk4 = k4./L(4);
+for i =1:length(fk1)
+  Pxx1_fk1(i) = 0;
+  Pxx2_fk1(i) = 0;
+  for m = 1:N
+    Pxx1_fk1(i)=Pxx1_fk1(i)+x1(m)*exp(-sqrt(-1)*2*%pi*(m-1)*fk1(i));
+    Pxx2_fk1(i)=Pxx1_fk1(i)+x1(m)*exp(-sqrt(-1)*2*%pi*(m-1)*fk1(i));
+  end
+  Pxx1_fk1(i) = (Pxx1_fk1(i)^2)/N;
+  Pxx2_fk1(i) = (Pxx2_fk1(i)^2)/N;
+end
+for i =1:length(fk2)
+  Pxx1_fk2(i) = 0;
+  Pxx2_fk2(i) = 0;
+  for m = 1:N
+    Pxx1_fk2(i)=Pxx1_fk2(i)+x1(m)*exp(-sqrt(-1)*2*%pi*(m-1)*fk2(i));
+    Pxx2_fk2(i)=Pxx1_fk2(i)+x1(m)*exp(-sqrt(-1)*2*%pi*(m-1)*fk2(i));
+  end
+  Pxx1_fk2(i) = (Pxx1_fk2(i)^2)/N;
+  Pxx2_fk2(i) = (Pxx1_fk2(i)^2)/N;
+end
+for i =1:length(fk3)
+  Pxx1_fk3(i) = 0;
+  Pxx2_fk3(i) = 0;
+  for m = 1:N
+    Pxx1_fk3(i) =Pxx1_fk3(i)+x1(m)*exp(-sqrt(-1)*2*%pi*(m-1)*fk3(i));
+    Pxx2_fk3(i) =Pxx1_fk3(i)+x1(m)*exp(-sqrt(-1)*2*%pi*(m-1)*fk3(i));
+  end
+  Pxx1_fk3(i) = (Pxx1_fk3(i)^2)/N;
+  Pxx2_fk3(i) = (Pxx1_fk3(i)^2)/N;
+end
+for i =1:length(fk4)
+  Pxx1_fk4(i) = 0;
+  Pxx2_fk4(i) = 0;
+  for m = 1:N
+    Pxx1_fk4(i) =Pxx1_fk4(i)+x1(m)*exp(-sqrt(-1)*2*%pi*(m-1)*fk4(i));
+    Pxx2_fk4(i) =Pxx1_fk4(i)+x1(m)*exp(-sqrt(-1)*2*%pi*(m-1)*fk4(i));
+  end
+  Pxx1_fk4(i) = (Pxx1_fk4(i)^2)/N;
+  Pxx2_fk4(i) = (Pxx1_fk4(i)^2)/N;
+end
+figure
+title('for frequency separation = 0.06')
+subplot(2,2,1)
+plot2d3('gnn',k1,abs(Pxx1_fk1))
+subplot(2,2,2)
+plot2d3('gnn',k2,abs(Pxx1_fk2))
+subplot(2,2,3)
+plot2d3('gnn',k3,abs(Pxx1_fk3))
+subplot(2,2,4)
+plot2d3('gnn',k4,abs(Pxx1_fk4))
+figure
+title('for frequency separation = 0.01')
+subplot(2,2,1)
+plot2d3('gnn',k1,abs(Pxx2_fk1))
+subplot(2,2,2)
+plot2d3('gnn',k2,abs(Pxx2_fk2))
+subplot(2,2,3)
+plot2d3('gnn',k3,abs(Pxx2_fk3))
+subplot(2,2,4)
+plot2d3('gnn',k4,abs(Pxx2_fk4))
diff --git a/830/CH12/EX12.5.1/Additive_Noise_Parameters.sce b/830/CH12/EX12.5.1/Additive_Noise_Parameters.sce
new file mode 100755
index 000000000..b59e316b7
--- /dev/null
+++ b/830/CH12/EX12.5.1/Additive_Noise_Parameters.sce
@@ -0,0 +1,26 @@
+//Graphical//
+//Example 12.5.1
+//Determination of power, frequency and varaince of
+//Additive noise
+clear;
+clc;
+close;
+ryy = [0,1,3,1,0];//Autocorrelation of signal
+cen_ter_value = ceil(length(ryy)/2);//center value of autocorrelation
+//Method1
+//TO find out the variance of the additive Noise
+C = ryy(ceil(length(ryy)/2):$);
+corr_matrix = toeplitz(C);//correlation matrix
+evals =spec(corr_matrix);//Eigen Values computation
+sigma_w = min(evals);//Minimum of eigen value = varinace of noise
+//Method2
+//TO find out the variance of the additive Noise
+P = [1,-sqrt(2),1];//Ploynomial in decreasing order
+Z = roots(P);//roots of the polynomial
+P1 = ryy(cen_ter_value+1)/real(Z(1));//power of the sinusoid
+A = sqrt(2*P1);//amplitude of the sinusoid
+sigma_w1 = ryy(cen_ter_value)-P1;//variance of noise method2
+disp(P1,'Power of the additive noise')
+f1 = acos(real(Z(1)))/(2*%pi)
+disp(f1,'frequency of the additive noise')
+disp(sigma_w1,'Variance of the additive noise')
-- 
cgit