Neural Network Toolbox

nnt2c

Update NNT 2.0 competitive layer

Syntax

net = nnt2c(PR,W,KLR,CLR)

Description

nnt2c(PR,W,KLR,CLR) takes these arguments,

• PR -- R x 2 matrix of min and max values for R input elements

  W -- S x R weight matrix

  KLR -- Kohonen learning rate, default = 0.01

  CLR -- Conscience learning rate, default = 0.001

and returns a competitive layer.

Once a network has been updated, it can be simulated, initialized, or trained with sim, init, adapt, and train.

See Also

newc

nncopy

nnt2elm

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