MATLAB: Neural Network Output :Scaling the output range.

neural networkneural networks

Hi,
The output layer of my neural network (3 layered) is using sigmoid as activation which outputs only in range [0-1]. However, if I want to train it for outputs that are beyond [0-1], say in thousands, what should I do?
For example if I want to train
input —-> output
0 0 ——> 0
0 1 ——> 1000
1000 1 —-> 1
1 1 ——-> 0
My program works for AND, OR, XOR etc. As input output are all in binary.
There were some suggestion to use,
Activation:
———–
y = lambda*(abs(x)*1/(1+exp(-1*(x))))
Derivative of activation:
————————-
lambda*(abs(y)*y*(1-y))
This did not converge for the mentioned training pattern. Are there any suggestion please?

Best Answer

Hello Greg,
Thanks again for answering the question. For my case, no rigid bound,
1. INCORRECT. ALL 3 VARIABLES ARE BOUNDED:
 0 <= X1, Y <= 1000
 0<= X2 <= 1.
2. HOWEVER, SINCE THE INPUT SCALES ARE DIFFERENT BY A FACTOR OF THOUSAND, X1 AND Y SHOULD BE TRANSFORMED BY VIA LOGS AND/OR POWERS. E.G.,
X1n = LOG10( 1 + X1 ) / LOG10( 1001 ) ==> 0 <= X1n <= 1
SIMILARLY FOR Y
HOPE THIS HELPS.
GREG
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