1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
|
<html><head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>arburg</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%">
<span class="previous"><a href="ar_psd.html"><< ar_psd</a></span>
</td>
<td width="40%" class="center">
<span class="top"><a href="section_cc2bc01c47967d47fcf3507a91d572ba.html">FOSSEE Signal Processing Toolbox</a></span>
</td>
<td width="30%" class="next">
<span class="next"><a href="arch_fit.html">arch_fit >></a></span>
</td>
</tr></table>
<hr />
</div>
<span class="path"><a href="index.html">FOSSEE Signal Processing Toolbox</a> >> <a href="section_cc2bc01c47967d47fcf3507a91d572ba.html">FOSSEE Signal Processing Toolbox</a> > arburg</span>
<br /><br />
<div class="refnamediv"><h1 class="refname">arburg</h1>
<p class="refpurpose">This function calculates coefficients of an autoregressive (AR) model of complex data.</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">arburg</span><span class="default">(</span><span class="default">x</span><span class="default">, </span><span class="default">poles</span><span class="default">)</span>
<span class="default">a</span><span class="default"> = </span><span class="functionid">arburg</span><span class="default">(</span><span class="default">x</span><span class="default">, </span><span class="default">poles</span><span class="default">, </span><span class="default">criterion</span><span class="default">)</span>
<span class="default">[</span><span class="default">a</span><span class="default">, </span><span class="default">v</span><span class="default">] = </span><span class="functionid">arburg</span><span class="default">(...)</span>
<span class="default">[</span><span class="default">a</span><span class="default">, </span><span class="default">v</span><span class="default">, </span><span class="default">k</span><span class="default">] = </span><span class="functionid">arburg</span><span class="default">(...)</span></pre></div></div>
<div class="refsection"><h3 class="title">Parameters</h3>
<dl><dt><span class="term">x:</span>
<dd><p class="para">vector of real or complex numbers, of length > 2</p></dd></dt>
<dt><span class="term">poles:</span>
<dd><p class="para">positive integer value < length(x) - 2</p></dd></dt>
<dt><span class="term">criterion:</span>
<dd><p class="para">string value, takes in "AKICc", "KIC", "AICc", "AIC" and "FPE", default it not using a model-selection criterion</p></dd></dt>
<dt><span class="term">a, v, k:</span>
<dd><p class="para">Output variables</p></dd></dt></dl></div>
<div class="refsection"><h3 class="title">Description</h3>
<p class="para">This is an Octave function.</p>
<p class="para">This function calculates coefficients of an autoregressive (AR) model of complex data x using the whitening lattice-filter method of Burg.</p>
<p class="para">The first argument is the data sampled. The second argument is the number of poles in the model (or limit in case a criterion is supplied).
The third parameter takes in the criterion to limit the number of poles. The acceptable values are "AIC", "AKICc", "KIC", "AICc" which are based on information theory.
Output variable a is a list of P+1 autoregression coefficients.
Output variable v is the mean square of residual noise from the whitening operation of the Burg lattice filter.
Output variable k corresponds to the reflection coefficients defining the lattice-filter embodiment of the model.</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">arburg</span><span class="scilabopenclose">(</span><span class="scilabopenclose">[</span><span class="scilabnumber">1</span><span class="scilabdefault">,</span><span class="scilabnumber">2</span><span class="scilabdefault">,</span><span class="scilabnumber">3</span><span class="scilabdefault">,</span><span class="scilabnumber">4</span><span class="scilabdefault">,</span><span class="scilabnumber">5</span><span class="scilabopenclose">]</span><span class="scilabdefault">,</span><span class="scilabnumber">2</span><span class="scilabopenclose">)</span>
<span class="scilabid">ans</span> <span class="scilaboperator">=</span>
<span class="scilabnumber">1.00000</span> <span class="scilaboperator">-</span><span class="scilabnumber">1.86391</span> <span class="scilabnumber">0.95710</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>
<br />
<div class="manualnavbar">
<table width="100%">
<tr><td colspan="3" class="next"><a href="http://bugzilla.scilab.org/enter_bug.cgi?product=Scilab%20software&component=Documentation%20pages" class="ulink">Report an issue</a></td></tr>
<tr>
<td width="30%">
<span class="previous"><a href="ar_psd.html"><< ar_psd</a></span>
</td>
<td width="40%" class="center">
<span class="top"><a href="section_cc2bc01c47967d47fcf3507a91d572ba.html">FOSSEE Signal Processing Toolbox</a></span>
</td>
<td width="30%" class="next">
<span class="next"><a href="arch_fit.html">arch_fit >></a></span>
</td>
</tr></table>
<hr />
</div>
</body>
</html>
|