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+<html><head>
+ <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
+ <title>ac2poly</title>
+ <style type="text/css" media="all">
+ @import url("scilab_code.css");
+ @import url("xml_code.css");
+ @import url("c_code.css");
+ @import url("style.css");
+ </style>
+ </head>
+ <body>
+ <div class="manualnavbar">
+ <table width="100%"><tr>
+ <td width="30%">
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+
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+ <td width="40%" class="center">
+ <span class="top"><a href="section_be19baaac84b122b8ad501d34462f5bf.html">FOSSEE Signal Processing Toolbox</a></span>
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+ <span class="path"><a href="index.html">FOSSEE Signal Processing Toolbox</a> &gt;&gt; <a href="section_be19baaac84b122b8ad501d34462f5bf.html">FOSSEE Signal Processing Toolbox</a> &gt; ac2poly</span>
+
+ <br /><br />
+ <div class="refnamediv"><h1 class="refname">ac2poly</h1>
+ <p class="refpurpose">Convert autocorrelation sequence to polynomial of prediction filter</p></div>
+
+
+<div class="refsynopsisdiv"><h3 class="title">Calling Sequence</h3>
+ <div class="synopsis"><pre><span class="default">a</span><span class="default"> = </span><span class="functionid">ac2poly</span><span class="default">(</span><span class="default">r</span><span class="default">)</span>
+<span class="default">[</span><span class="default">a</span><span class="default">,</span><span class="default">e</span><span class="default">] = </span><span class="functionid">ac2poly</span><span class="default">(</span><span class="default">r</span><span class="default">)</span></pre></div></div>
+
+<div class="refsection"><h3 class="title">Parameters</h3>
+ <dl><dt><span class="term">r:</span>
+ <dd><p class="para">Autocorrelation sequence to be represented with an FIR linear prediction filter</p></dd></dt>
+ <dt><span class="term">a:</span>
+ <dd><p class="para">Output polynomial representing the linear prediction filter e/(a(1) + a(2)z + a(3)z^2 .. a(N)z^N-1)</p></dd></dt>
+ <dt><span class="term">e:</span>
+ <dd><p class="para">Output scaling for the lienar prediction filter</p></dd></dt></dl></div>
+
+<div class="refsection"><h3 class="title">Description</h3>
+ <p class="para">Function ac2poly() finds the best fit polynomial for FIR linear prediction filter a, corresponding to the autocorrelation sequence r. a is the same length as r, and is normalized with the first element. So a(1) = 1.
+Author:
+Parthe Pandit</p>
+ <p class="para"></p></div>
+
+<div class="refsection"><h3 class="title">Bibliography</h3>
+ <p class="para">Kay, Steven M. Modern Spectral Estimation. Englewood Cliffs, NJ: Prentice-Hall, 1988.</p></div>
+ <br />
+
+ <div class="manualnavbar">
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