i am training the feedforward back propagation neural network using nntool in matlab with input vector of 12*304 and target vector of 1*304. Here is the list of parameters that I have used 2 hidden layers transfer function of (layer1,layer2,outputlayer)= logsig,logsig,tansig number of neurons(hiddenlayer1, hiddenlayer2)= 8,8
i tried many times. my epoches was less than 8. is this show a problem in my structure? in addition the error for the validation curveincreases with increasing epoch. is this show a wrong in nn structure?

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Greg Heath
Greg Heath le 5 Fév 2015

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The default structure is an I-H-O = 12-10-1 tansig/purelin fitnet. Standardize input and target with zscore. Try that configuration 10 times (10 different RNG states for data division and initial weights). If unsuccessful, systematically increase H. If validation stopping keeps occurring, try
net.divideFcn = '' % to get 100/0/0 data division.
Alternatively, since the default is
>> max_fail = net.trainParam.max_fail
max_fail = 6
Reset maxfail to a higher number
net.trainParam.max_fail = inf;
Hope this helps.
Thank you for formally accepting my answer
Greg

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