How can I build a 1x5x1 NN?

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Fernando Noguera
Fernando Noguera el 30 de Ag. de 2014
Respondida: Greg Heath el 22 de Sept. de 2014
Hi All, I am trying to build a FF NN with delay between layers to reproduce an abstract. My aim is to build the following 3 layers NN 1x5x1 with 5 delays taps between layers (5:5). So far this is the code I used to programmed but I'm not sure my code is building the network I want. Can anybody help me to check if my design is correct? if not, any correction I may need to do?
d1=(0:5);
d2=(0:5);
dtdnn_net=distdelaynet({d1,d2},5);
[p,Pi,Ai,t]=preparets(dtdnn_net,y2,y2);
dtdnn_net.trainFcn='trainbr';
dtdnn_net.trainParam.epochs=1000;
dtdnn_net.trainParam.lr=0.01;
dtdnn_net.layers{2}.size=1;
dtdnn_net=train(dtdnn_net,p,t);
yp=sim(dtdnn_net,p);
Thank you
  1 comentario
Greg Heath
Greg Heath el 31 de Ag. de 2014
Editada: Greg Heath el 31 de Ag. de 2014
Why did you post this without testing it on the data indicated in
help distdelaynet
?
Why didn't you use
view(net)
as indicated in the help and doc documentation?
doc distdelaynet
Why didn't you calculate the resulting resubstitution error?

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Greg Heath
Greg Heath el 22 de Sept. de 2014
[P,T] = simpleseries_dataset;
d1=(0:5);
d2=(0:5);
dtdnn_net = distdelaynet({d1,d2},5);
[Ps,Pi,Ai,Ts] = preparets(dtdnn_net,P,T);
ts = cell2mat(Ts);
MSE00s = var(ts',1) % 0.042348
dtdnn_net.trainFcn = 'trainbr';
dtdnn_net.trainParam.epochs = 1000;
dtdnn_net.trainParam.lr = 0.01;
dtdnn_net.layers{2}.size = 1;
rng('default')
[dtdnn_net tr Ys Es Xf Af] = train(dtdnn_net,Ps,Ts,Pi,Ai);
view(dtdnn_net)
%Ys = sim(dtdnn_net,Ps,Pi,Ai);
%Es = gsubtract(dtdnn_net,Ts,Ys)
es = cell2mat(Es);
R2s = 1-mse(es)/MSE00s % 0.9996
NOTE: Using net defaults with trainlm decreases learning time by a factor of 20

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