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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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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> and combines the component weight matrices bias vectors into a single row vector <CODE>w</CODE>. The facility to switch between these two representations for the network parameters is useful, for example, in training a network by error function minimization, since a single vector of parameters can be handled by general-purpose optimization routines. <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 the first-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>