Knowing the Weights in Matlab

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Scientist iitb
Scientist iitb el 18 de Jul. de 2011
I fitted the function using neural networks and after the computation is complete, I want to know the Final Weights and bias used after the optimisation process is complete. when I used the net.b command it is showing an array...which is not clear in terminology (P.S. net is name of my file)

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Mark Hudson Beale
Mark Hudson Beale el 9 de Sept. de 2011
The biases for each layer i are net.b{i}. So for a two layer network the biases are net.b{1} and net.b{2}.
The weights to layer i from input j are net.IW{i,j}. For a typical two layer network net.IW{1,1} will exist, while net.IW{2,1} will be empty because the input only goes to layer 1.
The weights to layer i from layer j are net.LW{i,j}. For a typical two layer network net.LW{2,1} will contain the weights to layer 2 from layer 1 and the other layer weights will be empty.
You should also take into account the input and output processing, if you are wanting to reproduce the input-output network function yourself. These functions and settings are available for a two layer network with these properties:
net.inputs{1}.processFcns
net.inputs{1}.processSettings
net.outputs{2}.processFcns
net.outputs{2}.processSettings

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