Timedelaynet output calculation principle

I have built a focused time-delay NN (two delays, 2 layers, hidden layer size of 2) and changed all the inputweights and layerweights to be zero (no bias is used). I would expect all zero output, but why the code give me nonzero values. Is there anybody can give suggestions on what's wrong? The simple code is shown as following:

clear;

numtaps = 2;

hiddenLayerSize = 2;

dyn_net = timedelaynet(1:numtaps,hiddenLayerSize);

dyn_net.trainFcn = 'trainlm';

dyn_net.layers{1}.transferFcn = 'tansig';

dyn_net.initFcn = 'initlay';

dyn_net.performFcn = 'mse';

dyn_net.biasConnect = [0;0];

dyn_net.trainParam.epochs = 1;

inputs = 0:0.1:1;

targets= 0:0.1:1;

inputs_1c = num2cell(inputs,1);

targets_1c = num2cell(targets,1);

[p,Pi,Ai,t] = preparets(dyn_net,inputs_1c,targets_1c);

[dyn_net,dyn_tr] = train(dyn_net,p,t,Pi,Ai);

dyn_net.IW{1,1} =[0 0;0 0];

dyn_net.LW{2,1} =[0 0];

output = dyn_net(p,Pi);

outputs1 = cell2mat(output); % I should expect zero, but the outputs are all 0.6.

dyn_net.LW{2,1}*tansig(dyn_net.IW{1,1}*(inputs(6:7)).') % This calculation gives me zero

Answer 1

[Greg Heath]

You did not include tHe 2 biases.

Hope this helps.

Greg

THANK YOU FOR FORMALLY ACCEPTING MY ANSWER

[Tingting Zhang]

Hi Greg,

Thanks for your answer. The configure of the NN is shown as following.

I intend not to include the bias just want to check the feedforward output calculation. I would expect that to be:

dyn_net.LW{2,1}*tansig(dyn_net.IW{1,1}*(inputs(k-1:-1:k-2)).').

But it is not the same as what I expect. So I manually change the inputweights and layerweights to be zero after training (before training gives me an error), and found nonzero output, that's weird.

I have also tried to include the bias as you suggested, the problem is still there.