Using of NARX in the case a time series step is not constant and inconsistent from one sample to another.
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I have 200 samples,each sample has 4 Inputs constant except time(a,b,c,(t1,t2,t3))and 1 Output (variable according to the t1,t2 and t3).The(t1,t2 and t3)is not consistent for all samples i.e. for first sample(t1=1 day,t2=40 day,t3=180 day),Second sample(t1=5 day,t2=55 day,t3=195 day) and so on..... My question: Is Narx(dynamic neural network) benefit to solve my problem and if not what is a appropriate architecture of ANN that i should use.I note that i use Toolbox of Matlab not a programming code.
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Accepted Answer
Greg Heath
on 12 Jun 2014
Terminology: You have 1 sample of 200 examples.
Do you mean you have 3 constanr inputs (a,b,c) ?
If so, ignore them and you will have
[ 3 200] = size(input)
[ 1 200] = size(output)
Unless there is a relatively constant correlation between the current output and past inputs and/or outputs, you have a simple regression problem. See
help fitnet
doc fitnet
Hope this helps.
Thank you for formally accepting my answer
Greg
More Answers (2)
Greg Heath
on 14 Jun 2014
[ 4 600 ] = size(input)
[ 1 600 ] = size(target)
help fitnet
doc fitnet
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