problem with configuration of neural network

hi I have a problem with using neural network. although I set all the parameter in 'trainparam' but it uses its default setting in training. the method that i set the parameter is as below: if true %

end
L=[4 8];
net=newcf(P,T,L);
net.trainparam.goal=1e-5;
net.trainParam.min_grad=1e-5;
net.trainparam.epochs=200;
net.trainFcn='traincgf';
net.layers{1}.transferFcn='tansig';
net.layers{2}.transferFcn='tansig';
[net,tr]=train(net,P,T);

Answer 1

[Greg Heath]

>> help newcf

   Create a cascade-forward backpropagation network.

   Obsoleted in R2010b NNET 7.0.  Last used in R2010a NNET 6.0.4.
   The recommended function is cascadeforwardnet.

Using the data in help and rng(0) to initialize the random number generator, I get

    close all, clear all, clc
    P = [0 1 2 3 4 5 6 7 8 9 10];
    T = [0 1 2 3 4 3 2 1 2 3 4];
    L=[4 8];
    net=newcf(P,T,L);

%Defaults

    net.trainparam.goal         % 0
    net.trainParam.min_grad     % 1e-5
    net.trainparam.epochs       % 1000
    net.trainFcn                % trainlm
    net.layers{1}.transferFcn   % tansig
    net.layers{2}.transferFcn   % tansig

%Assigned

    net.trainparam.goal        = 1e-5;
    net.trainParam.min_grad    = 1e-5;
    net.trainparam.epochs      = 200;
    net.trainFcn               = 'traincgf';
    net.layers{1}.transferFcn  = 'tansig';
    net.layers{2}.transferFcn  = 'tansig';

    rng(0)
    [net,tr,Y]=train(net,P,T);
    NMSE = mse(T-Y)/var(T,1)    % 0.2933

%Final

    net.trainparam.goal         % => 0
    net.trainParam.min_grad     % => 1e-10
    net.trainparam.epochs       % => 1000
    net.trainFcn                % traincgf
    net.layers{1}.transferFcn   % tansig
    net.layers{2}.transferFcn   % tansig

Which shows that goal, min_grad, and epochs have changed

However, only goal and epochs have changed to default values

Obviously, there are bugs.

The important thing is whether the normalized MSE is acceptable when longer data sets are used

Hope this helps.

Thank you for formally accepting my answer

Greg

[mehdi]

thanks for your attention I use matlab r2012a and i need to change the parameter to compare the neural network. how can i solve this bugs? with best regards