bp_innerloop.m

Inner loop of the backpropagtion learning algorithm.

One hidden layer. Uses tanh as the transfer function.



Uses the following global variables for input and/or output:

Inputs1 - input patterns

Desired - desired output patterns

LearnRate - learning rate parameter

Momentum - momentum parameter

DerivIncr - increment to the derivative of the transfer function

(Fahlman s trick typical value 0.2)

Weights1 - first weight layer (updated by this routine)

Weights2 - second weight layer (updated by this routine)

deltaW1 - initialize to 0 before first call

deltaW2 - initialize to 0 before first call

TSS - total sum-squared error (set by this routine)



Recurrent state-　bp_innerloop.m



　Inner loop of the backpropagtion learning algorithm.

　One hidden layer.　Uses tanh as the transfer function.



　Uses the following global variables for input and/or output:

　　 Inputs1　 -　input patterns

　　 Desired　 -　desired output patterns

　　 LearnRate -　learning rate parameter

　　 Momentum　-　momentum parameter

　　 DerivIncr -　increment to the derivative of the transfer function

　　　　　　　　　　(Fahlman s trick　typical value 0.2)

　　 Weights1　-　first weight layer (updated by this routine)

　　 Weights2　-　second weight layer (updated by this routine)

　　 deltaW1　 -　initialize to 0 before first call

　　 deltaW2　 -　initialize to 0 before first call

　　 TSS　　　 -　total sum-squared error (set by this routine)



　Recurrent state