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<refentry xml:id="tfrzam" 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:scilab="http://www.scilab.org"
          xmlns:ns3="http://www.w3.org/1999/xhtml"
          xmlns:mml="http://www.w3.org/1998/Math/MathML"
          xmlns:db="http://docbook.org/ns/docbook">


  <refnamediv>
    <refname>tfrzam</refname>
	<refpurpose>
		Zao-Atlas-Marks time-frequency distribution
	</refpurpose>
  </refnamediv>

<refsynopsisdiv>
   <title>Calling Sequence</title>
   <synopsis>
   	[TFR,T,F] = tfrzam(X)
   	[TFR,T,F] = tfrzam(X, T)
   	[TFR,T,F] = tfrzam(X, T, N)
   	[TFR,T,F] = tfrzam(X, T, N, G)
   	[TFR,T,F] = tfrzam(X, T, N, G, H)
   	[TFR,T,F] = tfrzam(X, T, N, G, H, TRACE)
   	[TFR,T,F] = tfrzam(...,'plot')
   </synopsis>
</refsynopsisdiv>

<refsection>
   <title>Parameters</title>
   <variablelist>
   <varlistentry>
     <term>X :</term>
     <listitem>
       <para> A Nx elements vector (auto-ZAM)  or a Nx by 2 array signal (cross-ZAM).</para>
     </listitem>
   </varlistentry>

   <varlistentry>
     <term> T:</term> 
     <listitem>
        <para> a real Nt vector with elements in [1 Nx] : time
          instant(s) on which the TFR is evaluated (default:
          1:NX).</para>
     </listitem>
   </varlistentry>

   <varlistentry>
     <term> N:</term> 
     <listitem><para> a positive integer: the number of frequency bins (default:NX).</para>
   </listitem>
   </varlistentry>

   <varlistentry>
     <term> G:</term> 
     <listitem>
       <para> a real vector with odd length: the time smoothing
       window, (default :Hamming(N/10)).</para>
       <para>It will be normalized such as the middle point equals 1.</para>
   </listitem>
   </varlistentry>

   <varlistentry>
     <term> H :</term> 
     <listitem>
       <para> real vector with odd length: the frequency smoothing
       window,(default: Hamming(N/4)).</para>
       <para>It will be normalized such as the middle point equals 1.</para>
   </listitem>
   </varlistentry>

   <varlistentry>
     <term> TRACE :</term> 
     <listitem>
       <para> if nonzero,the progression of the algorithm is shown
       (default : 0).</para>
     </listitem>
   </varlistentry>

   <varlistentry>
     <term>'plot':</term> <listitem><para> if one input parameter is
     'plot', <link linkend="tfrqview">tfrqview</link> is called and
     the time-frequency representation will be plotted.</para>
     </listitem>
   </varlistentry>

   <varlistentry>
     <term> TFR :</term> 
     <listitem>
       <para> A real N by Nt array: the time-frequency representation.</para>
     </listitem>
   </varlistentry>

   <varlistentry>
     <term> F :</term> 
     <listitem>
       <para> A N vector of normalized frequencies.</para>
     </listitem>
   </varlistentry>

   </variablelist>
</refsection>

<refsection>
   <title>Description</title>
   <para>
tfrzam computes the Zao-Atlas-Marks distribution of a discrete-time
signal X, or the cross Zao-Atlas-Marks representation between two
signals.
</para>
</refsection>

<refsection>
   <title>Examples</title>
   <programlisting role="example"><![CDATA[
sig = fmlin(128,0.05,0.3) + fmlin(128,0.15,0.4);
g = window("kr",9,3*%pi); 
h = window("kr",27,3*%pi);
[TFR,T,F] = tfrzam(sig,1:128,128,g,h);
clf; gcf().color_map = jetcolormap(128);
Sgrayplot(T,F,TFR');
   ]]></programlisting>
  <scilab:image><![CDATA[
sig = fmlin(128,0.05,0.3) + fmlin(128,0.15,0.4);
g = window("kr",9,3*%pi); 
h = window("kr",27,3*%pi);
[TFR,T,F] = tfrzam(sig,1:128,128,g,h);
clf; gcf().color_map = jetcolormap(128);
Sgrayplot(T,F,TFR');
    ]]></scilab:image>
</refsection>

<refsection>
   <title>Authors</title>
   <simplelist type="vert">
   <member>H. Nahrstaedt - Aug 2010</member>
   <member>	F. Auger, May-August 1994, July 1995.</member>
   <member>	Copyright (c) 1996 by CNRS (France).</member>
   </simplelist>
</refsection>
</refentry>
