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Update NNT 2.0 self-organizing map to NNT 3.0
net = nnt2som(pr,[d1 d2 ...],w,olr,osteps,tlr,tnd)
nnt2som(PR,[D1,D2,...],W,OLR,OSTEPS,TLR,TND) takes these arguments,
PR - R x 2 matrix of min and max values for R input elements.
Di - Size of ith layer dimension.
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.
nnt2som assumes that the self-organizing map has a grid topology (gridtop) using link distances (linkdist). This corresponds with the nbman neighborhood function in NNT 2.0.
The new network will only output 1 for the neuron with the greatest net input. In NNT 2.0 the network would also output 0.5 for that neuron's neighbors.
Once a network has been updated it can be simulated, initialized, adapted, or trained with sim, init, adapt, and train.
newsom