Neural network weight and bias initializaiton problem

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I'm cresting a neural network in one part of my program and using it's weights and biases for another neural network in other part so I have these codes:
net_b = patternnet(10);
net_b = configure(net,INPUT,Target);
Weights = getwb(net);
I will use this neural network weights and biases for creating another neural network as below:
net = patternnet(10);
net = configure(net,INPUT,Target);
net = setwb(net,Weights);
Everything is good until this stage but now I want disable pre-processing from neural network (Because I did it in one of stages of my program before insert the data to the neural network) So I will use these functions:
When I use two above functions to remove processing and after that check weights in inputs layer or biases in output layer everything will remove and I have an empty matrix but in hidden layer everything is normal. How can I do these without removing my weights and biases?

Accepted Answer

Greg Heath
Greg Heath on 14 Aug 2014
net = patternnet(10);
net.inputs{1}.processFcns = {};
net.outputs{2}.processFcns = {};
net = configure(net,INPUT,Target);
net = setwb(net,Weights);
IW = net.IW
b = net.b
LW = net.LW
Hope this helps.
Thank you for formally accepting my answer

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