| Neural Network Toolbox | |
Syntax
Description
nnt2p(PR,W,B,TF,LF) takes these arguments,
PR - R x 2 matrix of min and max values for R input elements.
W - S x R weight matrix.
B - S x 1 bias vector.
TF - Transfer function, default = 'hardlim'.
LF - Learning function, default = 'learnp'.
The transfer function TF can be hardlim or hardlims. The learning function LF can be learnp or learnpn.
Once a network has been updated, it can be simulated, initialized, adapted, or trained with sim, init, adapt, and train.
See Also
| | nnt2lvq | nnt2rb | |