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<div class="refnamediv"><h1 class="refname">poly2ac</h1>
<p class="refpurpose">Convert prediction polynomial to autocorrelation sequence.</p></div>
<div class="refsynopsisdiv"><h3 class="title">Calling Sequence</h3>
<div class="synopsis"><pre><span class="default">R</span><span class="default"> = </span><span class="functionid">poly2ac</span><span class="default">(</span><span class="default">a</span><span class="default">,</span><span class="default">efinal</span><span class="default">)</span></pre></div></div>
<div class="refsection"><h3 class="title">Parameters</h3>
<dl><dt><span class="term">a:</span>
<dd><p class="para">input prediction polynomial with 1st element 1 (if not, poly2ac normalizes it to 1 before proceeding).</p></dd></dt>
<dt><span class="term">efinal:</span>
<dd><p class="para">input prediction error</p></dd></dt>
<dt><span class="term">r:</span>
<dd><p class="para">output autocorrelation sequence</p></dd></dt></dl></div>
<div class="refsection"><h3 class="title">Description</h3>
<p class="para">This function obtains the underlying autocorrelation sequence that would best fit a linear prediction filter described by the
denominator polynomial and the numerator scaling. The filter is H(z) = efinal/(a(1) + a(2) x z a(3) x z^2 ... a(n) x z^n-1)</p>
<p class="para"></p></div>
<div class="refsection"><h3 class="title">Examples</h3>
<div class="programlisting"><table border="0" width="100%"><tr><td width="98%"><pre class="scilabcode"><span class="scilabid">a</span> <span class="scilaboperator">=</span> <span class="scilabopenclose">[</span><span class="scilabnumber">1.0000</span> <span class="scilabnumber">0.4288</span> <span class="scilabnumber">0.76</span> <span class="scilabnumber">0.0404</span> <span class="scilaboperator">-</span><span class="scilabnumber">0.02</span><span class="scilabopenclose">]</span><span class="scilabdefault">;</span>
<span class="scilabid">efinal</span> <span class="scilaboperator">=</span> <span class="scilabnumber">0.2</span><span class="scilabdefault">;</span> <span class="scilabcomment">// Step prediction error</span>
<span class="scilabid">r</span> <span class="scilaboperator">=</span> <span class="scilabid">poly2ac</span><span class="scilabopenclose">(</span><span class="scilabid">a</span><span class="scilabdefault">,</span><span class="scilabid">efinal</span><span class="scilabopenclose">)</span> <span class="scilabcomment">// Autocorrelation sequence</span></pre></td><td valign="top"><a href="scilab://scilab.execexample/"><img src="ScilabExecute.png" border="0"/></a></td><td valign="top"><a href="scilab://scilab.editexample/"><img src="ScilabEdit.png" border="0"/></a></td><td></td></tr></table></div></div>
<div class="refsection"><h3 class="title">See also</h3>
<ul class="itemizedlist"><li class="member"><a href="ac2poly.html" class="link">ac2poly</a></li>
<li class="member"><a href="poly2rc.html" class="link">poly2rc</a></li>
<li class="member"><a href="rc2poly.html" class="link">rc2poly</a></li>
<li class="member"><a href="rc2ac.html" class="link">rc2ac</a></li>
<li class="member"><a href="ac2rc.html" class="link">ac2rc</a></li>
<li class="member"><a href="scilab://Author:" class="link">Parthe Pandit</a></li></ul></div>
<div class="refsection"><h3 class="title">Bibliography</h3>
<p class="para">S. Kay, Modern Spectral Estimation, Prentice Hall, N.J., 1987, Chapter 6.</p></div>
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