Incorrect Neural Network output calculation through weights! Help!

Hi guys, I confront a problem calculating Neural Network Outputs manually through weights.

The NN has the below specifications: 

    Input Size 7 
    1 Hidden Layer of Size 10 
    Output Size 10

I trained the network train(network,Inputs,Targets) with trainFcn = 'trainlm' and network.layers{1}.transferFcn = 'satlins'. Others defaults.

After training I extracted the weights with the commands below:

b1 = cell2mat(network.b(1));   %Table size 10x1 
IW = cell2mat(network.IW);     %Table size 10x7 
b2 = cell2mat(network.b(2));   %Table size 10x1 
LW = cell2mat(network.LW);     %Table size 10x10

but when I tried for an input X=[1,1,1,1,1,1,1]':

out1 = purelin( LW * (satlins(IW * X + b1)) + b2 ); 
out2=network(X);

I took different results out1~=out2.

I have searched similar problems but I cannot adapt them to my problem. Could you help me? Thanks.

Answer 1

[Greg Heath]

You did not take into account the default mapminmax normalization of inputs and outputs.

Hope this helps.

Thank you for formally accepting my answer

Greg

[Nikos Vasileiadis]

Thank you Greg! Could you be more specific on how I can modify my calculation to have the right result? I tried to do something like this:

out1 = mapminmax (purelin( LW * (satlins(IW * mapminmax (X) + b1)) + b2 ));

but it didn't work.