By including a moving window of fixed length in the input vector of MLP, is the Back-propagation ANN equivalent to NAR model?

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If this is the case, how we can add the moving window? Supposing that the lag is equal to 3, for example:
N= lenght(data);
d=timestep ahead;
input = data( 1:N-d); % No transpose;
target = data( 1+d : N );
MSE00 = var(target',1) % Reference MSE
net = fitnet; % default H = 10
net.divideParam.valRatio = 10/100;
net.divideParam.testRatio = 20/100;
[net tr output error ] = train(net, input, target);
%output = net(input);
error = target - output;
NMSE = mse(error)/MSE00 % Range [ 0 1 ]
R2 = 1- NMSE

Respuesta aceptada

Greg Heath
Greg Heath el 15 de Nov. de 2015
1. When you insert code try to make sure it runs.
N= lenght(data); % ERROR
d=timestep ahead; % ERROR
2. Replace TRAIN with ADAPT
Hope this helps.
Thank you for formally accepting my answer
  2 comentarios
coqui el 18 de Nov. de 2015
thank you Greg.
I only have 1 series, I have used FITNET. To continue beyond the original data (for example, 50 points) how I can do it?
Greg Heath
Greg Heath el 18 de Nov. de 2015
Editada: Greg Heath el 18 de Nov. de 2015
I have several posts on predicting data beyond the target region. Let me know if you can't find any of them.

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