I would like to know how the winning neuron is selected by the NEWSOM function within Neural Network Toolbox.
Prashant Kumar answered . 2024-04-27 13:27:49
net = newsom(PR,[d1,d2,...],tfcn,dfcn,olr,osteps,tlr,tns)
Description
Competitive layers are used to solve classification problems.
NET = NEWSOM(PR,[D1,D2,...],TFCN,DFCN,OLR,OSTEPS,TLR,TNS) takes,
PR - Rx2 matrix of min and max values for R input elements.
Di - Size of ith layer dimension, defaults = [5 8].
TFCN - Topology function, default = 'hextop'.
DFCN - Distance function, default = 'linkdist'.
OLR - Ordering phase learning rate, default = 0.9.
OSTEPS - Ordering phase steps, default = 1000.
TLR - Tuning phase learning rate, default = 0.02;
TND - Tuning phase neighborhood distance, default = 1.
and returns a new self-organizing map.
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