Using discrete Fourier series to train ANN's

Greetings, r/MachineLearning,

I'm a self-taught non-math/cs undergrad, quite new to the field, but trying to get better at it, because it fascinates me. So I had this idea for my term paper: use EEG, transform the recordings using STFT and trying to use that as a more computation friendly representation of the data in training the network. However I ran into a problem: discrete Fourier series of a single STFT are [n by 3] vectors (where n is the number of harmonics) and as far as I know, that can't be used to train ANN's. You need one training example to be a row/column vector. Has anyone else encountered such a problem and/or has any idea how to come up with a solution, a suitable data representation, if any?

Cheers!