MATLAB: Initialize weights and biases in a nureal network

neural networks

How can i initialize weights and biases in a feed forward neural network which built with newff command to arbitrary values before training?

Best Answer

The call to NEWFF automatically creates random initial weights via INITNW. Just remember to initialize RAND before the first call to NEWFF so that you can duplicate your results.

Greg

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MATLAB: How to train a feedfordward neural network with error weights

 Use the command window
 help mse
 doc mse

Hope this helps.

Thank you for formally accepting my answer

Greg

MATLAB: Weights don’t initialize.

No.

Multilayer percetron doesn't contain 'hardlim'(hardlim -is capable to classify only linearly separable set. Two or more layers in network - aren't separable linearly. ). Using 'logsig'.

The equivalent network - multilayer percetron.

P =[0 1 0 1; 0 0 1 1];
T = [0 0 0 1];
net=newff(minmax(P),[2,10,1],{'logsig','logsig','logsig'},'trainbfg');
net.trainParam.epochs = 100;
net = init (net);
net.IW{1,1}, net.IW{2,1}, 
  net.LW{3,2}
  net.b{1}, net.b{3}
net=train(net,P,T);
a = sim(net,P)

'trainbfg' – back propagation learning.

Error in network design.

Best Answer

Related Solutions

MATLAB: How to train a feedfordward neural network with error weights

MATLAB: Weights don’t initialize.

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