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Different inputDelays and feedbackDelays for NARXNET network

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Arthur B
Arthur B el 18 de Feb. de 2021
Editada: Arthur B el 18 de Feb. de 2021
Hello all the Matlab community,
It is the second day I've been looking for an answer in the forum, especially at Greg's answers, and I can confidently post this question since I still haven't found the answer...
I'm trying to define a NARXNET with different inut and feedback delays. For that I have generated a NARX script from the ntstool, and am modifying the generated script.
Typicaly, I want my delays to be:
inputDelays = 0:5;
feedbackDelays = 6:11;
hiddenLayerSize = 10;
net = narxnet(inputDelays,feedbackDelays,hiddenLayerSize,'open',trainFcn);
This is because in my situation, I use input data x(t) to x(t-5) and I can only know my output before another 5 timesteps have passed, therefore I can only look back at the previous output y(t-6) to y(t-11).
In the script, it is possible to inform those delays (like I have earlier), but I have a doubt concerning the fact that the network understands them and really trains the network the way I intent it to be trained. The reason why I have doubts is because when I prepare the timeseries with
[x,xi,ai,t] = preparets(net,X,{},T);
and I check x, then I see x{1,1) = X{12} and x{2,1} = T{12}, when I would have expected x{1,1) = X{1} and x{2,1} = T{7}. Of course there is the same wrong representation of delays on xi.
So, questions:
  • does my doubt come from a wrong understanding of how the timeseries are prepared for the narxnet, or is the narxnet indeed not prepared like would like?
  • can anyone confirm that the delays as I have defined them will be understood by the narxnet?
  • I wanted to try and investigate the net structure using analyseNetwork(net) in the hope I would see exactly which values are fed and how, but it doesn't work for narxnet network. Any alternative?
  • on top of having different delays for input and feedback, is it possible to have different spans? I am thinking: inputDelays = 0:5 and feedbackDelays = 6:20.
Thanks all!

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