Predict a parabola with LSTM deep learning

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Giacomo Notaro
Giacomo Notaro on 17 Mar 2020
Edited: Giacomo Notaro on 17 Mar 2020
Hi all,
I'm testing deep learning LSTM networks and I'm trying to predict a parabola, which is a non periodic function, after having succeeded in predicting periodic ones.
I obtained the first two curves with these settings:
numFeatures = 1;
numResponses = 1;
numHiddenUnits = 200;
layers = [ ...
sequenceInputLayer(numFeatures)
bilstmLayer(numHiddenUnits)
fullyConnectedLayer(numResponses)
regressionLayer];
options = trainingOptions('adam', ...
'MaxEpochs',500, ...
'GradientThreshold',1, ...
'InitialLearnRate',0.005, ...
'LearnRateSchedule','piecewise', ...
'SequenceLength','longest',...
'LearnRateDropPeriod',1250, ...
'LearnRateDropFactor',0.2, ...
'Verbose',0, ...
'Plots','training-progress');
The third one is what I would like to obtain, and this is possible using LSTM as explained here, where some people has done it in python.
I'm wondering how to obtain the same with LSTM layer in MATLAB

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