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wolffd@0 1 <html>
wolffd@0 2 <head>
wolffd@0 3 <title>
wolffd@0 4 Netlab Reference Manual somfwd
wolffd@0 5 </title>
wolffd@0 6 </head>
wolffd@0 7 <body>
wolffd@0 8 <H1> somfwd
wolffd@0 9 </H1>
wolffd@0 10 <h2>
wolffd@0 11 Purpose
wolffd@0 12 </h2>
wolffd@0 13 Forward propagation through a Self-Organising Map.
wolffd@0 14
wolffd@0 15 <p><h2>
wolffd@0 16 Synopsis
wolffd@0 17 </h2>
wolffd@0 18 <PRE>
wolffd@0 19
wolffd@0 20 d2 = somfwd(net, x)
wolffd@0 21 </PRE>
wolffd@0 22
wolffd@0 23
wolffd@0 24 <p><h2>
wolffd@0 25 Description
wolffd@0 26 </h2>
wolffd@0 27 <CODE>d2 = somfwd(net, x)</CODE> propagates the data matrix <CODE>x</CODE> through
wolffd@0 28 a SOM <CODE>net</CODE>, returning the squared distance matrix <CODE>d2</CODE> with
wolffd@0 29 dimension <CODE>nin</CODE> by <CODE>num_nodes</CODE>. The $i$th row represents the
wolffd@0 30 squared Euclidean distance to each of the nodes of the SOM.
wolffd@0 31
wolffd@0 32 <p><CODE>[d2, win_nodes] = somfwd(net, x)</CODE> also returns the indices of the
wolffd@0 33 winning nodes for each pattern.
wolffd@0 34
wolffd@0 35 <p><h2>
wolffd@0 36 Example
wolffd@0 37 </h2>
wolffd@0 38
wolffd@0 39 <p>The following code fragment creates a SOM with a $5times 5$ map for an
wolffd@0 40 8-dimensional data space. It then applies the test data to the map.
wolffd@0 41 <PRE>
wolffd@0 42
wolffd@0 43 net = som(8, [5, 5]);
wolffd@0 44 [d2, wn] = somfwd(net, test_data);
wolffd@0 45 </PRE>
wolffd@0 46
wolffd@0 47
wolffd@0 48 <p><h2>
wolffd@0 49 See Also
wolffd@0 50 </h2>
wolffd@0 51 <CODE><a href="som.htm">som</a></CODE>, <CODE><a href="somtrain.htm">somtrain</a></CODE><hr>
wolffd@0 52 <b>Pages:</b>
wolffd@0 53 <a href="index.htm">Index</a>
wolffd@0 54 <hr>
wolffd@0 55 <p>Copyright (c) Ian T Nabney (1996-9)
wolffd@0 56
wolffd@0 57
wolffd@0 58 </body>
wolffd@0 59 </html>