I used nftool in Matlab 2012 and trained a network. I gave the training inputs as x=[250:1] and targets as t=[250:1]. I used 10 hidden layers. I trained the network and got the results and exported the data to workspace. I finally got net as the variable in the workspace. I want to realize this network in hardware. So, I want the exact weights and bias values. I searched the net and typed net.IW and got 10 values, net.LW and got yet another 10 values and net.b and got 11 values. My network diagram is as shown below:

Output Neural Net

If IW is the Input Weight and LW is the Layer Weight, I realized the network diagram as shown below:

My realization of output Neural Network

I got 10 values for IW, which would fit into 10 hidden layers, and 10 values for LW, which will fit into 10 hidden layers according to my realization. I got 11 values for bias, which will fit in to my network, since there are 11 (b) blocks in the network. But, i am missing one IW and one LW value.

I want to know whether there is a mistake in my realization of the output of the network or I missed any of the values. Please help.

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    $\begingroup$ Looks like you have one hidden layer with ten neurons and not ten hidden layers. $\endgroup$ – Aaron Feb 1 '14 at 20:50
  • $\begingroup$ @Aaron No, in the second picture, Hidden is not my editing. So, its 10 hidden layers only. I also specified 10 hidden layers during training. $\endgroup$ – sundar Feb 2 '14 at 7:10

If I understand correctly your IW should be [1*10] as it takes 1-dim input to 10-dim hidden layer than LW should be [10*1] as it takes 10-dim hidden to 1-dim output, b should be 10 for the hidden layer and 1 for the output layer

Why do you think your'e missing something?

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