Neural Network Toolbox

nnt2elm

Update NNT 2.0 Elman backpropagation network

Syntax

net = nnt2elm(PR,W1,B1,W2,B2,BTF,BLF,PF)

Description

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

  B1 -- S1 x 1 bias vector

  W2 -- S2 x S1 weight matrix

  B2 -- S2 x 1 bias vector

  BTF -- Backpropagation network training function, default = 'traingdx'

  BLF -- Backpropagation weight/bias learning function, default = 'learngdm'

  PF -- Performance function, default = 'mse'

and returns a feed-forward network.

The training function BTF can be any of the backpropagation 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.

See Also

newelm

nnt2c

nnt2ff

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