nnt2c

Purpose

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, adapted, or trained with sim, init, adapt, or train.

See Also

newc

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