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<html><head> <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1"> <title>kernel.m</title><link rel="stylesheet" type="text/css" href="../../m-syntax.css"></head><body><code><span class=defun_kw>function</span> <span class=defun_out>K </span>= <span class=defun_name>kernel</span>(<span class=defun_in>varargin</span>)<br><span class=h1>% KERNEL Evaluates kernel function.</span><br><span class=help>%</span><br><span class=help>% <span class=help_field>Synopsis:</span></span><br><span class=help>% K = kernel(X,ker,arg)</span><br><span class=help>% K = kernel(X1,X2,ker,arg)</span><br><span class=help>%</span><br><span class=help>% <span class=help_field>Description:</span></span><br><span class=help>% K = kernel( X, ker, arg ) returns kernel matrix K [n x n] </span><br><span class=help>%</span><br><span class=help>% K(i,j) = k(X(:,i),X(:,j)) for all i=1..n, j=1..n,</span><br><span class=help>%</span><br><span class=help>% where k: a x b -> R is a kernel function given by </span><br><span class=help>% identifier ker and argument arg:</span><br><span class=help>% </span><br><span class=help>% Identifier Name Definition</span><br><span class=help>% 'linear' ... linear kernel k(a,b) = a'*b</span><br><span class=help>% 'poly' ... polynomial k(a,b) = (a'*b+arg[2])^arg[1]</span><br><span class=help>% 'rbf' ... RBF (Gaussian) k(a,b) = exp(-0.5*||a-b||^2/arg[1]^2)</span><br><span class=help>% 'sigmoid' ... Sigmoidal k(a,b) = tanh(arg[1]*(a'*b)+arg[2])</span><br><span class=help>%</span><br><span class=help>% K = kernel( X1, X2, ker, arg ) returns kernel matrix K [n1 x n2]</span><br><span class=help>% </span><br><span class=help>% K(i,j) = k(X1(:,i),X2(:,j)) for all i=1..n1, j=1..n2,</span><br><span class=help>%</span><br><span class=help>% <span class=help_field>Input:</span></span><br><span class=help>% X [dim x n] Single matrix of input vectors.</span><br><span class=help>% X1 [dim x n1], X2 [dim x n2] Pair of input matrices.</span><br><span class=help>% ker [string] Kernel identifier.</span><br><span class=help>% arg [1 x narg] Kernel argument.</span><br><span class=help>%</span><br><span class=help>% <span class=help_field>Output:</span></span><br><span class=help>% K [n1 x n1] or K [n1 x n2] Kernel matrix.</span><br><span class=help>% </span><br><span class=help>% <span class=help_field>Example:</span></span><br><span class=help>% X = rand(2,50);</span><br><span class=help>% K = kernel( X, 'rbf', 1);</span><br><span class=help>% figure; pcolor( K );</span><br><span class=help>%</span><br><span class=help>% See also:</span><br><span class=help>% DIAGKER, KERNELPROJ.</span><br><span class=help>%</span><br><hr><span class=help1>% <span class=help1_field>About:</span> Statistical Pattern Recognition Toolbox</span><br><span class=help1>% (C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac</span><br><span class=help1>% <a href="http://www.cvut.cz">Czech Technical University Prague</a></span><br><span class=help1>% <a href="http://www.feld.cvut.cz">Faculty of Electrical Engineering</a></span><br><span class=help1>% <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a></span><br><br><span class=help1>% <span class=help1_field>Modifications:</span></span><br><span class=help1>% 19-sep-2004, VF</span><br><span class=help1>% 5-may-2004, VF</span><br><br><hr><span class=comment>% MEX-File function. </span><br></code>?? 快捷鍵說明
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