to prove the robustness of neural network model what is the best model which can compare to it ? (especially in order to forecast)
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to prove the robustness of neural network model what is the best model which can compare to it ?
can you propose a model?
THANKS
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Accepted Answer
Greg Heath
on 18 Nov 2015
No.
I measure robustness by adding increasing levels of noise to the input.
Hope this helps.
Greg
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Greg Heath
on 5 Dec 2015
Which timeseries function are you using? Timedelay, or Narx?
Either way, add noise at a fixed SNR to the input and plot output error vs SNR.
[I N ] = size(input0)
var0 = mean(var(input0'))
input = input0 + sqrt(var0/SNR)*randn(I,N);
Hope this helps.
Thank you for formally accepting my answer
Greg
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