Neural network weight and bias initializaiton problem

Hi.

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:

    net.inputs{1}.processFcns={};
    net.outputs{2}.processFcns={};

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?

Thanks.

Answer 1

[Greg Heath]

 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

Greg

[Jack]

Thank you for your answer Greg.