Hey everybody,
I am a beginner in Neural Networks and I need help with a model for my problem.
I want to classify waveforms into two categories (Binary basically) and I am having a difficult time training an NN for this task.
I have 600 one-dimensional waveforms, each one is 10,000 points long. I have processed them with an RFFT. Each waveform either belongs to class True or False.
Here is a plot of those classes (after RFFT):

Data True II.jpg1800×800 108 KB

https://www.photobox.co.uk/my/photo/full?photo_id=500630831842 5
(Sorry, New users can only post one image.)
As you can see, the waveforms are visibly different. I want to train a Neural Network to classify a given waveform to either class.
I have tried a two-layer CNN but the most I could get was 67% accuracy. I also have tried an LSTM but I think I made lots of mistake in their design.
Here I am, looking for help for a model.
Thank you guys