Is it possible to use deep learning on small number of samples but each sample has a large amount data?
You have a database of 50x6 currently.

When you run a exercise of deep learning on images, you have n (images) x (width(px) x height(px) x 3) variables.

You have similarly characterized dataset when you use the wavelet transforms, so it is possible. You have to be very cautious because you will have more variables than n, so the danger of overfitting increases a lot.