MATLAB: Prediction of the Sinus Function using Neural Networks

Deep Learning Toolboxneural networkpredictionsinus

My objective is to create a NN that is able to predict the sinus function. For that I tried using several types of networks, including feed-forward using the Fit Tool and NARX net using the time series tool.
The sinus has a period of 365.
Using Fiting Tool(default configurations except i give it 5 neurons)
%The input I give for training is:
  input = linspace(1,270,100); % I used several variations of this
  target = sin(2*pi*input/365);
%Results:  Samples    MSE        R
%Training:   70     7.23e-7   9.9999e-1
%Validation: 15     6.84e-7   9.9999e-1
%Testing:    15     3.171e-6  9.99993e-1
Which I think look pretty good.
In the next step I try to predict the remaining function using the following sample:
pred_inp=linspace(271,365,100);
pred_targ= sin(2*pi*pred_inp/365);
 % Results:  Samples    MSE           R
 %             100    1.33175e-0  -3.6286e-1 
%And this is where it gets crazy, sometimes it gives a good prediction, 
%other times it just goes down.
%It gets even worse if I try to predict for more than one period:
pred_inp=linspace(271,730,100);
I have no idea of what is going wrong. Anyone here could assist me? Or showing me another way to do this?

Best Answer

The rule of thumb for predicting a sinusoid function is (I think) that you have to train on at least 1.5 periods with at least 8 points per period. If this turns out to be wrong, try training on 2 periods with 20 points per period. Then back off.
Hope this helps.
Greg
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