I designed a very simple dnn, whose structure is shown in the figure.
featureInputLayer(40000);
And the code i used to generate my trainset —— 2D signals and 2D signals affected by noise, I have put this .m file as an attachment. I want to be able to use neural networks to remove noise from the signal.
When I input my training set to train it, the system prompts me that there is an error.
featureInputLayer(40000);
options = trainingOptions('adam', ...
'InitialLearnRate',0.001,...
'LearnRateSchedule','piecewise',...
'LearnRateDropFactor',0.9,...
'LearnRateDropPeriod',40,...
'ExecutionEnvironment', 'cpu', ...
'ValidationData',{VaSet_o,VaSet_n},...
'L2Regularization',1.0000e-05,...
'Shuffle', 'every-epoch', ...
'Plots', 'training-progress', ...
net = trainNetwork(TrainSet_n, TrainSet_o, layers, options);
Error using trainNetwork
Invalid validation data. The output size (100) of the last layer does not match the response size (40000).
Invalid training data. The output size (100) of the last layer does not match theresponse size (40000).
I am quite sure that the response size of my training set is 100 instead of 40000
OK, then I change the output size to 40000 but didn't modify my train set.
And the system the system told me that another error occurred.
The output size (40000) of the last layer does not match the response size (100).
Now how does the response size change back to 100????
WHY??????????
I really hope someone can help me, please.
This is very important to me.
