I'm curious if learning from features in the complex domain is better than 
learning from magnitude spectra or other common compromises made when using 
comp valued training data. I read somewhere once that there was a 
noticeable difference in models trained using a 2 real numbers vs actually 
using a complex number. The literature surrounding complex valued ANNs 
is... sparse.

 
I'm not familiar with the C code portions of Theano. Where would I start 
looking to get familiar with this? I'm guessing at present there's no code 
to represent a complex matrix in a GPUArray? Or if there is basic things 
like broadcasting, multiplying, etc will need to be implemented first. 
Gradients would then follow. Then complex valued models would be possible...

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