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wolffd@0 1 <html>
wolffd@0 2 <head>
wolffd@0 3 <title>
wolffd@0 4 Netlab Reference Manual mlpfwd
wolffd@0 5 </title>
wolffd@0 6 </head>
wolffd@0 7 <body>
wolffd@0 8 <H1> mlpfwd
wolffd@0 9 </H1>
wolffd@0 10 <h2>
wolffd@0 11 Purpose
wolffd@0 12 </h2>
wolffd@0 13 Forward propagation through 2-layer network.
wolffd@0 14
wolffd@0 15 <p><h2>
wolffd@0 16 Synopsis
wolffd@0 17 </h2>
wolffd@0 18 <PRE>
wolffd@0 19 y = mlpfwd(net, x)
wolffd@0 20 [y, z] = mlpfwd(net, x)
wolffd@0 21 [y, z, a] = mlpfwd(net, x)
wolffd@0 22 </PRE>
wolffd@0 23
wolffd@0 24
wolffd@0 25 <p><h2>
wolffd@0 26 Description
wolffd@0 27 </h2>
wolffd@0 28 <CODE>y = mlpfwd(net, x)</CODE> takes a network data structure <CODE>net</CODE> together with
wolffd@0 29 a matrix <CODE>x</CODE> of input vectors, and forward propagates the inputs
wolffd@0 30 through the network to generate a matrix <CODE>y</CODE> of output
wolffd@0 31 vectors. Each row of <CODE>x</CODE> corresponds to one input vector and each
wolffd@0 32 row of <CODE>y</CODE> corresponds to one output vector.
wolffd@0 33
wolffd@0 34 <p><CODE>[y, z] = mlpfwd(net, x)</CODE> also generates a matrix <CODE>z</CODE> of the hidden
wolffd@0 35 unit activations where each row corresponds to one pattern.
wolffd@0 36
wolffd@0 37 <p><CODE>[y, z, a] = mlpfwd(net, x)</CODE> also returns a matrix <CODE>a</CODE>
wolffd@0 38 giving the summed inputs to each output unit, where each row
wolffd@0 39 corresponds to one pattern.
wolffd@0 40
wolffd@0 41 <p><h2>
wolffd@0 42 See Also
wolffd@0 43 </h2>
wolffd@0 44 <CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="mlppak.htm">mlppak</a></CODE>, <CODE><a href="mlpunpak.htm">mlpunpak</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>
wolffd@0 45 <b>Pages:</b>
wolffd@0 46 <a href="index.htm">Index</a>
wolffd@0 47 <hr>
wolffd@0 48 <p>Copyright (c) Ian T Nabney (1996-9)
wolffd@0 49
wolffd@0 50
wolffd@0 51 </body>
wolffd@0 52 </html>