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Update NNT 2.0 Elman backpropagation network to NNT 3.0
net = nnt2elm(pr,w1,b1,w2,b2,btf,blf,pf)
nnt2elm(PR,W1,B1,W2,B2,BTF,BLF,PF) takes these arguments,
PR - R x 2 matrix of min and max values for R input elements.
W1 - S1 x (R+S1) weight matrix.
BTF - Backprop network training function, default = 'traingdx'.
BLF - Backprop weight/bias learning function, default = 'learngdm'.
PF - Performance function, default = 'mse'.
BTF can be any of the backprop training functions such as traingd, traingdm, traingda, and traingdx. Large step-size algorithms, such as trainlm, are not recommended for Elman networks.
The learning function BLF can be either of the backpropagation learning functions such as learngd or learngdm.
The performance function can be any of the differentiable performance functions such as mse or msereg.
Once a network has been updated it can be simulated, initialized, adapted, or trained with sim, init, adapt, and train.
newelm