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