[Neural network] How does neural network calculate output from net.IW, net.LW, net.b ?

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Example I have a trained neural network as following
clear all
clc
[ x, t ] = simplefit_dataset;
net = feedforwardnet;
rng('default')
net = configure(net,x,t);
[net,tr,y,e] = train(net,x,t);
After training finished, weights will be save to net.IW, net.LW, net.b
How does the network calculate output from these weights ?
If output can be calculated as :
y=[ones(Ns,1) tansig([ones(Ns,1) x]*W1')] * W2'
Where Ns is number of training samples.
How can W1 and W2 be formed from net.IW, net.LW and net.b ?

Accepted Answer

Greg Heath
Greg Heath on 8 Dec 2014
I will let you figure out how to do it when the default normalization and de-normalization are not removed:
clear all, clc
[ x, t ] = simplefit_dataset;
[ I N ] = size(x) %[ 1 94 ]
[ O N ] = size(t) %[ 1 94 ]
net = fitnet; % H=10 default
rng('default') % For repeatability
% net = configure(net,x,t); % For multiple designs
A = net.input.processFcns % see below
B = net.output.processFcns % see below
% processFcns = {'removeconstantrows' 'mapminmax'}
net.input.processFcns = { }; % Remove normalization
net.output.processFcns= { };
[net,tr,y,e] = train(net,x,t);
R2 = 1-mse(e)/var(t,1) % 0.99998
IW = net.IW{1,1}
b1 = net.b{1}
b2 = net.b{2}
LW = net.LW{2,1}
y1 = b2 + LW * tansig( b1 * ones(1,N) + IW * x );
dy = max(abs(y1-y)) %2.6645e-15
Hope this helps.
Thank you for formally accepting my answer
Greg
  3 Comments
Greg Heath
Greg Heath on 10 Dec 2014
It is better to just use the random weights assigned by the program.
Otherwise, reverse the above assignment statements. For example
net.IW{1,1}= 0.01*randn(H,I);
for I input nodes and H hidden nodes.
Asaduz Zaman
Asaduz Zaman on 27 Jul 2016
Helped me a lot. Couldn't find why
sim(net,input)
and
classify(net,input)
wasn't producing same response as I'm new in NNTool. Now I got it. Thanks again.

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More Answers (1)

Greg Heath
Greg Heath on 2 May 2018
You did not consider
net.input.processFcns
and
net.output.processFcns
Search in ANSWERS and
comp.soft-sys.matlab
Hope this helps.
Greg

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