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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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<html> <head> <title> Netlab Reference Manual somfwd </title> </head> <body> <H1> somfwd </H1> <h2> Purpose </h2> Forward propagation through a Self-Organising Map. <p><h2> Synopsis </h2> <PRE> d2 = somfwd(net, x) </PRE> <p><h2> Description </h2> <CODE>d2 = somfwd(net, x)</CODE> propagates the data matrix <CODE>x</CODE> through a SOM <CODE>net</CODE>, returning the squared distance matrix <CODE>d2</CODE> with dimension <CODE>nin</CODE> by <CODE>num_nodes</CODE>. The $i$th row represents the squared Euclidean distance to each of the nodes of the SOM. <p><CODE>[d2, win_nodes] = somfwd(net, x)</CODE> also returns the indices of the winning nodes for each pattern. <p><h2> Example </h2> <p>The following code fragment creates a SOM with a $5times 5$ map for an 8-dimensional data space. It then applies the test data to the map. <PRE> net = som(8, [5, 5]); [d2, wn] = somfwd(net, test_data); </PRE> <p><h2> See Also </h2> <CODE><a href="som.htm">som</a></CODE>, <CODE><a href="somtrain.htm">somtrain</a></CODE><hr> <b>Pages:</b> <a href="index.htm">Index</a> <hr> <p>Copyright (c) Ian T Nabney (1996-9) </body> </html>