What is the meaning for InputDelays and FeedbackDelays in Neural Network time series prediction?
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Hi all,
I'm a littile confused about the meaning of InputDelays and FeedbackDelays in NN time series prediction. Actually, in the example of NARX prediction, InputDelays=1:2, FeedbackDelays=1:2, I wonder how to determine these two values and what these values extactly mean? Any suggestion is highly appreciated.
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Accepted Answer
Greg Heath
on 30 Oct 2013
y(t) = f(x(t-id:t-1),y(t-fd:t-1);
Good input feedback delays can be obtained by finding the significant delays of the input-target cross correlation function.
Good output feedback delays can be obtained by finding the significant delays of the target autocorrelation function.
I have posted several examples in the NEWSGROUP and ANSWERS.
Searching the two word phrase significant delay seems a good place to start.
Hope this helps.
Greg
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Greg Heath
on 31 Oct 2013
Regularization via the mse option or trainbr can be used to mitigate the fact that there are more unknown weights than equations. I think it is most used for smaller data sets whose data division subsets would not be sufficiently large for reliable design and estimation of performance on unseen non-training data.
If you wish to make a few comparison designs, please use MATLAB data
help nndatasets
so that we can compare results.
Greg Heath
on 21 May 2014
I have never seen trainbr used for timeseries nets. I use either dividetrain or divideblock with the default trainlm.
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