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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/REC-html40/loose.dtd"><html><head> <title>Description of mvfilter</title> <meta name="keywords" content="mvfilter"> <meta name="description" content="Multi-variate filter function"> <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1"> <meta name="generator" content="m2html © 2003 Guillaume Flandin"> <meta name="robots" content="index, follow"> <link type="text/css" rel="stylesheet" href="../m2html.css"></head><body><a name="_top"></a><div><a href="../index.html">Home</a> > <a href="index.html">tsa</a> > mvfilter.m</div><!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png"> Master index</a></td><td align="right"><a href="index.html">Index for tsa <img alt=">" border="0" src="../right.png"></a></td></tr></table>--><h1>mvfilter</h1><h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>Multi-variate filter function</strong></div><h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>function [x,z]=mvfilter(B,A,x,z) </strong></div><h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="fragment"><pre class="comment"> Multi-variate filter function Y = MVFILTER(B,A,X) [Y,Z] = MVFILTER(B,A,X,Z) Y = MVFILTER(B,A,X) filters the data in matrix X with the filter described by cell arrays A and B to create the filtered data Y. The filter is a "Direct Form II Transposed" implementation of the standard difference equation: a0*Y(n) = b0*X(n) + b1*X(n-1) + ... + bq*X(n-q) - a1*Y(n-1) - ... - ap*Y(:,n-p) A=[a0,a1,a2,...,ap] and B=[b0,b1,b2,...,bq] must be matrices of size Mx((p+1)*M) and Mx((q+1)*M), respectively. X must be of size N*M a0,a1,...,ap, b0,b1,...,bq are matrices of size MxM a0 is usually the identity matrix I or must be invertible A multivariate inverse filter can be realized with [AR,RC,PE] = mvar(Y',P); e = mvfilter([eye(M),-AR],eye(M),Y); see also: <a href="mvar.html" class="code" title="function [ARF,RCF,PE,DC,varargout] = mvar(Y, Pmax, Mode);">MVAR</a>, FILTER</pre></div><!-- crossreference --><h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>This function calls:<ul style="list-style-image:url(../matlabicon.gif)"><li><a href="mvfilter.html" class="code" title="function [x,z]=mvfilter(B,A,x,z)">mvfilter</a> Multi-variate filter function</li></ul>This function is called by:<ul style="list-style-image:url(../matlabicon.gif)"><li><a href="mvar.html" class="code" title="function [ARF,RCF,PE,DC,varargout] = mvar(Y, Pmax, Mode);">mvar</a> Estimates Multi-Variate AutoRegressive model parameters</li><li><a href="mvfilter.html" class="code" title="function [x,z]=mvfilter(B,A,x,z)">mvfilter</a> Multi-variate filter function</li></ul><!-- crossreference --><hr><address>Generated on Tue 17-Aug-2004 00:13:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/">m2html</a></strong> © 2003</address></body></html>⌨️ 快捷键说明
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