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initsompc

Initialize SOM weights with principal components

Syntax

weights = initsom(inputs,dimensions,positions)
weights = initsom(inputs,dimensions,topologyFcn)

Description

initsompc initializes the weights of an N-dimensional self-organizing map so that the initial weights are distributed across the space spanned by the most significant N principal components of the inputs. Distributing the weight significantly speeds up SOM learning, as the map starts out with a reasonable ordering of the input space.

weights = initsom(inputs,dimensions,positions) takes these arguments:

inputs

R-by-Q matrix of Q R-element input vectors

dimensions

D-by-1 vector of positive integer SOM dimensions

positions

D-by-S matrix of S D-dimension neuron positions

and returns the following:

weights

S-by-R matrix of weights

weights = initsom(inputs,dimensions,topologyFcn) is an alternative specifying the name of a layer topology function instead of positions. topologyFcn is called with dimensions to obtain positions.

Examples

inputs = rand(2,100)+[2;3]*ones(1,100);
dimensions = [3 4];
positions = gridtop(dimensions);
weights = initsompc(inputs,dimensions,positions);

See Also

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