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<html><head> <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1"> <title>Contents.m</title><link rel="stylesheet" type="text/css" href="../../stpr.css"></head><body><table border=0 width="100%" cellpadding=0 cellspacing=0><tr valign="baseline"><td valign="baseline" class="function"><b class="function">RBFPREIMG2</b><td valign="baseline" align="right" class="function"><a href="../../kernels/preimage/index.html" target="mdsdir"><img border = 0 src="../../up.gif"></a></table> <p><b>RBF pre-image problem by Gradient optimization.</b></p> <hr><div class='code'><code><span class=help></span><br><span class=help> <span class=help_field>Synopsis:</span></span><br><span class=help> z = rbfpreimg2(model)</span><br><span class=help> z = rbfpreimg2(model,options)</span><br><span class=help></span><br><span class=help> <span class=help_field>Description:</span></span><br><span class=help> z = rbfpreimg2(model) it uses gradient method to solve </span><br><span class=help> the pre-image problem for the Radial Basis Function (RBF) </span><br><span class=help> kernel. The function 'fminunc' of the Matlab Optimization </span><br><span class=help> toolbox is exploited for 1D search along the gradient </span><br><span class=help> direction.</span><br><span class=help></span><br><span class=help> z = rbfpreimg2(model,options) use to specify the control</span><br><span class=help> parameters of the gradient optimization.</span><br><span class=help> </span><br><span class=help> <span class=help_field>Input:</span></span><br><span class=help> model [struct] Kernel expansion:</span><br><span class=help> .Alpha [num_data x 1] Weight vector.</span><br><span class=help> .sv.X [dim x num_data] Vectors determining the kernel expansion.</span><br><span class=help> .options.arg [1x1] Argument of the RBF kernel (see 'help kernel').</span><br><span class=help></span><br><span class=help> options [struct] Control parameters:</span><br><span class=help> .min_improvement [1x1] Minimal allowed improvement of the objective </span><br><span class=help> function in two consecutive steps (default 1e-3).</span><br><span class=help> options.start_t [1x1] Starting value of the 1D search procedure </span><br><span class=help> (default 1e-3).</span><br><span class=help></span><br><span class=help> <span class=help_field>Output:</span></span><br><span class=help> z [dim x 1] Found preimage.</span><br><span class=help></span><br><span class=help> <span class=also_field>See also </span><span class=also></span><br><span class=help><span class=also> <a href = "../../kernels/preimage/rbfpreimg.html" target="mdsbody">RBFPREIMG</a>, <a href = "../../kernels/preimage/rbfpreimg3.html" target="mdsbody">RBFPREIMG3</a>, <a href = "../../kernels/rsrbf.html" target="mdsbody">RSRBF</a>, <a href = "../../kernels/extraction/kpcarec.html" target="mdsbody">KPCAREC</a>.</span><br><span class=help></span><br></code></div> <hr> <b>Source:</b> <a href= "../../kernels/preimage/list/rbfpreimg2.html">rbfpreimg2.m</a> <p><b class="info_field">About: </b> Statistical Pattern Recognition Toolbox<br> (C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac<br> <a href="http://www.cvut.cz">Czech Technical University Prague</a><br> <a href="http://www.feld.cvut.cz">Faculty of Electrical Engineering</a><br> <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a><br> <p><b class="info_field">Modifications: </b> <br> 10-jun-2004, VF<br> 03-dec-2003, VF<br></body></html>⌨️ 快捷键说明
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