Error in running 1d cnn
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% Train Basic 1D-CNN %
% Prepare XTrain,YTrain (signal,label)
%% TODO %%
XTrain = load('D:\Trishita\VAD_NN\voicedregion_signal');
YTrain= load('D:\Trishita\VAD_NN\voicedregion_label');
chunklength = 1000;
% numberofchunks = floor(length(XTrain)/chunklength);
numberofchunks = 1;
XTrain = reshape(XTrain(1:numberofchunks*chunklength),chunklength,1,numberofchunks);
YTrain = reshape(YTrain(1:numberofchunks*chunklength),chunklength,1,numberofchunks);
XValidation = load('D:\Trishita\VAD_NN\voicedregion_signal');
YValidation= load('D:\Trishita\VAD_NN\voicedregion_label');
chunklength = 1000;
% numberofchunks = floor(length(XValidation)/chunklength);
numberofchunks = 1;
XValidation = reshape(XValidation(1:numberofchunks*chunklength),chunklength,1,1,numberofchunks);
YValidation = reshape(YValidation(1:numberofchunks*chunklength),chunklength,1,1,numberofchunks);
% define network %
layers = [
% input signal chunk - 1000x1
imageInputLayer([1000 1 1])
convolution2dLayer([3,1],1,'Padding','same')
reluLayer
convolution2dLayer([3,1],32,'Padding','same')
reluLayer
convolution2dLayer([3,1],32,'Padding','same')
reluLayer
convolution2dLayer([3,1],32,'Padding','same')
reluLayer
fullyConnectedLayer(1000)
regressionLayer
];
% define training options
miniBatchSize = 128;
validationFrequency = 8000;
options = trainingOptions('sgdm', ...
'MiniBatchSize',miniBatchSize, ...
'MaxEpochs',30, ...
'InitialLearnRate',1e-3, ...
'LearnRateSchedule','piecewise', ...
'LearnRateDropFactor',0.1, ...
'LearnRateDropPeriod',20, ...
'Shuffle','every-epoch', ...
'ValidationData',{XValidation,YValidation}, ...
'ValidationFrequency',validationFrequency, ...
'Plots','training-progress', ...
'Verbose',false);
% train and wait
net = trainNetwork(XTrain,YTrain,layers,options);
My error is: XTrain =
reshape(XTrain(1:numberofchunks*chunklength),chunklength,1,numberofchunks);
>> BasicCNN
Index exceeds array bounds.
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Shengjie Ren
am 13 Jun. 2020
Is the matlab program of 1D-CNN implemented? Is it easy to share? Thank you so much.1653482142@qq.com
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