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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 gaussianLog</title> <meta name="keywords" content="gaussianLog"> <meta name="description" content="gaussianLog: Multi-dimensional log Gaussian propability density function"> <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> > gaussianLog.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>gaussianLog</h1><h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>gaussianLog: Multi-dimensional log Gaussian propability density 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 out = gaussianLog(data, gaussianParam, gConst); </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"> gaussianLog: Multi-dimensional log Gaussian propability density function
Usage: out = gaussianLog(data, gaussianParam, gConst)
data: d x n data matrix, representing n data vector of dimension d
mu: d x 1 vector
sigma: d x d matrix
d x 1 vector
1 x 1 scalar
out: 1 x n vector
See also "gaussian".</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="gaussian.html" class="code" title="function out = gaussian(data, gParam);">gaussian</a> gaussian: Multi-dimensional Gaussian propability density function</li><li><a href="gaussianLog.html" class="code" title="function out = gaussianLog(data, gaussianParam, gConst);">gaussianLog</a> gaussianLog: Multi-dimensional log Gaussian propability density function</li></ul>This function is called by:<ul style="list-style-image:url(../matlabicon.gif)"><li><a href="gaussianLog.html" class="code" title="function out = gaussianLog(data, gaussianParam, gConst);">gaussianLog</a> gaussianLog: Multi-dimensional log Gaussian propability density function</li></ul><!-- crossreference --><h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><ul style="list-style-image:url(../matlabicon.gif)"><li><a href="#_sub1" class="code">function selfdemo</a></li></ul><h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="fragment"><pre>0001 <a name="_sub0" href="#_subfunctions" class="code">function out = gaussianLog(data, gaussianParam, gConst);</a>0002 <span class="comment">% gaussianLog: Multi-dimensional log Gaussian propability density function</span>0003 <span class="comment">% Usage: out = gaussianLog(data, gaussianParam, gConst)</span>0004 <span class="comment">% data: d x n data matrix, representing n data vector of dimension d</span>0005 <span class="comment">% mu: d x 1 vector</span>0006 <span class="comment">% sigma: d x d matrix</span>0007 <span class="comment">% d x 1 vector</span>0008 <span class="comment">% 1 x 1 scalar</span>0009 <span class="comment">% out: 1 x n vector</span>0010 <span class="comment">%</span>0011 <span class="comment">% See also "gaussian".</span>0012 0013 <span class="comment">% Roger Jang, 20050327</span>0014 0015 <span class="keyword">if</span> nargin<1, <a href="#_sub1" class="code" title="subfunction selfdemo">selfdemo</a>; <span class="keyword">return</span>; <span class="keyword">end</span>0016 [dim, dataNum]=size(data); 0017 0018 dataMinusMu = data-repmat(gaussianParam.mu, 1, dataNum);0019 <span class="keyword">if</span> prod(size(gaussianParam.sigma))==1 <span class="comment">% identity covariance matrix times a constant for each Gaussian</span>0020 <span class="keyword">if</span> nargin<30021 out = -sum(dataMinusMu.*dataMinusMu/gaussianParam.sigma, 1)/2-dim/2*log(2*pi)-dim/2*log(gaussianParam.sigma);0022 <span class="keyword">else</span>0023 out = -sum(dataMinusMu.*dataMinusMu/gaussianParam.sigma, 1)/2+gConst;0024 <span class="keyword">end</span>0025 <span class="keyword">elseif</span> prod(size(gaussianParam.sigma))==dim <span class="comment">% diagonal covariance matrix for each Gaussian</span>0026 <span class="keyword">if</span> nargin<30027 out = -sum(dataMinusMu./repmat(gaussianParam.sigma, 1, dataNum).*dataMinusMu, 1)/2-dim/2*log(2*pi)-log(prod(gaussianParam.sigma))/2;0028 <span class="keyword">else</span>0029 out = -sum(dataMinusMu./repmat(gaussianParam.sigma, 1, dataNum).*dataMinusMu, 1)/2+gConst;0030 <span class="keyword">end</span>0031 <span class="keyword">else</span> <span class="comment">% full covariance matrix for each Gaussian</span>0032 invCov = inv(gaussianParam.sigma); <span class="comment">% For repeated invocation of this function, this step should be moved out of this function</span>0033 <span class="keyword">if</span> nargin<30034 out = -sum(dataMinusMu.*(invCov*dataMinusMu), 1)/2-dim/2*log(2*pi)-log(det(gaussianParam.sigma))/2;0035 <span class="keyword">else</span>0036 out = -sum(dataMinusMu.*(invCov*dataMinusMu), 1)/2+gConst;0037 <span class="keyword">end</span>0038 <span class="keyword">end</span>0039 0040 <span class="comment">% ====== Self demo</span>0041 <a name="_sub1" href="#_subfunctions" class="code">function selfdemo</a>0042 x = linspace(-10, 10);0043 gaussianParam.mu = 0;0044 gaussianParam.sigma = 0.1;0045 0046 y1 = log(<a href="gaussian.html" class="code" title="function out = gaussian(data, gParam);">gaussian</a>(x, gaussianParam));0047 y2 = <a href="gaussianLog.html" class="code" title="function out = gaussianLog(data, gaussianParam, gConst);">gaussianLog</a>(x, gaussianParam);0048 diff = abs(y1-y2);0049 0050 subplot(2,1,1); plot(x, y1, x, y2);0051 subplot(2,1,2); plot(x, diff);</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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