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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 gmmGrowDemo</title> <meta name="keywords" content="gmmGrowDemo"> <meta name="description" content="Example of using gmmGrow.m for growing a GMM (gaussian mixture models)."> <meta http-equiv="Content-Type" content="text/html; charset=big5"> <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">dcpr</a> > gmmGrowDemo.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 dcpr <img alt=">" border="0" src="../right.png"></a></td></tr></table>--><h1>gmmGrowDemo</h1><h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>Example of using gmmGrow.m for growing a GMM (gaussian mixture models).</strong></div><h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>This is a script file. </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"> Example of using gmmGrow.m for growing a GMM (gaussian mixture models).</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="dcData.html" class="code" title="function DS = dcdata(dataID)">dcData</a> DCDATA Test data sets for data clustering (no class label).</li><li><a href="gmmEval.html" class="code" title="function [logProb, gaussianProb] = gmmEval(data, gmmParam);">gmmEval</a> gmmEval: Evaluation of a GMM (Gaussian mixture model)</li><li><a href="gmmGrow.html" class="code" title="function gmmParam=gmmGrow(gmmParam, targetGaussianNum)">gmmGrow</a> gmmGrow: Grow gaussians within a GMM</li><li><a href="gmmTrain.html" class="code" title="function [gmmParam, logProb] = gmmTrain(data, gaussianNumCovType, gmmTrainParam)">gmmTrain</a> gmmTrain: Parameter training for gaussian mixture model (GMM)</li><li><a href="gmmTrainParamSet.html" class="code" title="function gmmTrainParam=gmmTrainParamSet">gmmTrainParamSet</a> The following parameters are used for gmmTrain()</li></ul>This function is called by:<ul style="list-style-image:url(../matlabicon.gif)"><li><a href="gmmGrow.html" class="code" title="function gmmParam=gmmGrow(gmmParam, targetGaussianNum)">gmmGrow</a> gmmGrow: Grow gaussians within a GMM</li></ul><!-- crossreference --><h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="fragment"><pre>0001 <span class="comment">% Example of using gmmGrow.m for growing a GMM (gaussian mixture models).</span>0002 0003 DS = <a href="dcData.html" class="code" title="function DS = dcdata(dataID)">dcData</a>(2);0004 data=DS.input;0005 gaussianNum=1;0006 covType=3;0007 gmmTrainParam=<a href="gmmTrainParamSet.html" class="code" title="function gmmTrainParam=gmmTrainParamSet">gmmTrainParamSet</a>;0008 gmmTrainParam.useKmeans=1;0009 gmmTrainParam.dispOpt=1;0010 gmmTrainParam.maxIteration=500;0011 0012 <span class="keyword">for</span> i=1:50013 close all;0014 [gmmParam, lp] = <a href="gmmTrain.html" class="code" title="function [gmmParam, logProb] = gmmTrain(data, gaussianNumCovType, gmmTrainParam)">gmmTrain</a>(data, [gaussianNum, covType], gmmTrainParam);0015 gaussianNum=2*gaussianNum;0016 gmmParam = <a href="gmmGrow.html" class="code" title="function gmmParam=gmmGrow(gmmParam, targetGaussianNum)">gmmGrow</a>(gmmParam, gaussianNum);0017 <span class="keyword">end</span>0018 0019 pointNum = 40;0020 x = linspace(min(data(1,:)), max(data(1,:)), pointNum);0021 y = linspace(min(data(2,:)), max(data(2,:)), pointNum);0022 [xx, yy] = meshgrid(x, y);0023 data = [xx(:) yy(:)]';0024 z = <a href="gmmEval.html" class="code" title="function [logProb, gaussianProb] = gmmEval(data, gmmParam);">gmmEval</a>(data, gmmParam);0025 zz = reshape(z, pointNum, pointNum);0026 figure; mesh(xx, yy, zz); axis tight; box on; rotate3d on0027 figure; contour(xx, yy, zz, 30); axis image</pre></div><hr><address>Generated on Thu 30-Oct-2008 12:53:56 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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