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<div class="refnamediv"><h1 class="refname">arcov</h1>
<p class="refpurpose">Autoregressive all-pole model parameters — covariance method</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">arcov</span><span class="default">(</span><span class="default">x</span><span class="default">,</span><span class="default">p</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">arcov</span><span class="default">(</span><span class="default">x</span><span class="default">,</span><span class="default">p</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">contains normalized estimates of the AR system parameters, A(z), in descending powers of z.</p></dd></dt>
<dt><span class="term">e:</span>
<dd><p class="para">variance estimate of the white noise input to the AR model</p></dd></dt>
<dt><span class="term">x:</span>
<dd><p class="para">is the input signal</p></dd></dt>
<dt><span class="term">p:</span>
<dd><p class="para">is the order of the auto regressive model</p></dd></dt></dl></div>
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