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Netlab Reference Manual mlppak
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<H1> mlppak
</H1>
<h2>
Purpose
</h2>
Combines weights and biases into one weights vector.

<p><h2>
Synopsis
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<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)


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