1 files changed, 1 insertions, 75 deletions
diff --git a/help/en_US/levinson.xml b/help/en_US/levinson.xml
index ac340a6..056795f 100644
--- a/help/en_US/levinson.xml
+++ b/help/en_US/levinson.xml
@@ -17,81 +17,7 @@
 
   <refnamediv>
     <refname>levinson</refname>
-    <refpurpose>Levinson-Durbin Recurssion Algorithm</refpurpose>
-    <para> </para>
+    <refpurpose></refpurpose>
   </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>