I have to classify a time series signal with a CNN (not a LSTM or some kind of RNN). The input signal is a window with a width of 90 samples (currently, but can be changed) and 59 sensor values. So my signal can be represented by a 90x59 matrix for a single class. I have 28 classes.
Now I´m looking for a good solution to classify this. My first try ends in a very poor result of 24% accuracy and I´m thinking of multi channel models for all 59 channels in my model.
Is there any good way to start for some kind of good prediction results?