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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 enter image description here

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 enter image description here

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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Ok. Assuming a feed-forward network with N inputs, M hidden neurons and K outputs you have: - into IW{1} a M x N weight matrix (from input to hidden layer) - into LW{2} a K x M weigth matrix (from hidden to output layer) - into b all the biases

You can also have a look into getx source code (type open getx), that's a deprecated function replaced by getwb but more easy to understand.

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