wolffd@0: wolffd@0: wolffd@0: wolffd@0: Netlab Reference Manual somfwd wolffd@0: wolffd@0: wolffd@0: wolffd@0:

somfwd wolffd@0:

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wolffd@0: Purpose wolffd@0:

wolffd@0: Forward propagation through a Self-Organising Map. wolffd@0: wolffd@0:

wolffd@0: Synopsis wolffd@0:

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wolffd@0: 
wolffd@0: d2 = somfwd(net, x)
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wolffd@0: Description wolffd@0:

wolffd@0: d2 = somfwd(net, x) propagates the data matrix x through wolffd@0: a SOM net, returning the squared distance matrix d2 with wolffd@0: dimension nin by num_nodes. The $i$th row represents the wolffd@0: squared Euclidean distance to each of the nodes of the SOM. wolffd@0: wolffd@0:

[d2, win_nodes] = somfwd(net, x) also returns the indices of the wolffd@0: winning nodes for each pattern. wolffd@0: wolffd@0:

wolffd@0: Example wolffd@0:

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The following code fragment creates a SOM with a $5times 5$ map for an wolffd@0: 8-dimensional data space. It then applies the test data to the map. wolffd@0:

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wolffd@0: net = som(8, [5, 5]);
wolffd@0: [d2, wn] = somfwd(net, test_data);
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wolffd@0: See Also wolffd@0:

wolffd@0: som, somtrain

wolffd@0: Pages: wolffd@0: Index wolffd@0:

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