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<html><head><title>Netlab Reference Manual mlppak</title></head><body><H1> mlppak</H1><h2>Purpose</h2>Combines weights and biases into one weights vector.<p><h2>Synopsis</h2><PRE>w = mlppak(net)</PRE><p><h2>Description</h2><CODE>w = mlppak(net)</CODE> takes a network data structure <CODE>net</CODE> andcombines the component weight matrices bias vectors into a single rowvector <CODE>w</CODE>. The facility to switch between these tworepresentations for the network parameters is useful, for example, intraining a network by error function minimization, since a singlevector of parameters can be handled by general-purpose optimizationroutines.<p>The ordering of the paramters in <CODE>w</CODE> is defined by<PRE> w = [net.w1(:)', net.b1, net.w2(:)', net.b2];</PRE>where <CODE>w1</CODE> is the first-layer weight matrix, <CODE>b1</CODE> is thefirst-layer bias vector, <CODE>w2</CODE> is the second-layer weight matrix,and <CODE>b2</CODE> is the second-layer bias vector.<p><h2>See Also</h2><CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="mlpunpak.htm">mlpunpak</a></CODE>, <CODE><a href="mlpfwd.htm">mlpfwd</a></CODE>, <CODE><a href="mlperr.htm">mlperr</a></CODE>, <CODE><a href="mlpbkp.htm">mlpbkp</a></CODE>, <CODE><a href="mlpgrad.htm">mlpgrad</a></CODE><hr><b>Pages:</b><a href="index.htm">Index</a><hr><p>Copyright (c) Ian T Nabney (1996-9)</body></html>⌨️ 快捷键说明
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