Thread Subject:

weight in neural network

Hello Sir,
           Sir if i have tried the following code, the problem if I generate W1 and W2 then weights net.IW{1,1} and net.LW{2,1} are diffrenet and if i dont use W1 and W2 then net.IW{1,1} and net.LW{2,1} are different. Sir how the weights are related
with W1 and W2 ?


s = RandStream('mcg16807','Seed', 0);
RandStream.setDefaultStream(s)
x=sinimfin; %input
t=t; %target
S1=1; % number of hidden layers
S2=2; % number of output layers (= number of classes)
[R,Q]=size(x);
W1= rand(S1,R);
W2= rand(S2,S1);
net = patternnet(4);
net = train(net,x,t);
% view(net)
y=net(x);
plotconfusion(t,y);
perf=mse(y-t);