06 Nov 2002
02 Dec 2002)
Pattern analysis toolbox.
function [d2, win_nodes] = somfwd(net, x)
%SOMFWD Forward propagation through a Self-Organising Map.
% D2 = SOMFWD(NET, X) propagates the data matrix X through a SOM NET,
% returning the squared distance matrix D2 with dimension NIN by
% NUM_NODES. The $i$th row represents the squared Euclidean distance
% to each of the nodes of the SOM.
% [D2, WIN_NODES] = SOMFWD(NET, X) also returns the indices of the
% winning nodes for each pattern.
% See also
% SOM, SOMTRAIN
% Copyright (c) Ian T Nabney (1996-2001)
% Check for consistency
errstring = consist(net, 'som', x);
% Turn nodes into matrix of centres
nodes = (reshape(net.map, net.nin, net.num_nodes))';
% Compute squared distance matrix
d2 = dist2(x, nodes);
% Find winning node for each pattern: minimum value in each row
[w, win_nodes] = min(d2, , 2);