[faust1706]

Sorry about the late response. I had my last round of tests before finals these past two weeks. I was having corruption problems with my git repo so I deleted it and made a new one of the same name.

I got rid of neural-net.cpp and added a tester.cpp for easy testing. I also appear to have fixed the training issue, kind of. It worked 5 out of 5 times for me using th (tanh) on the xor data. I'll have to look into sigmoid.

It isn't optimized, but it will work. It's not intended to be used for deep learning or anything. The most I could see an FRC team use is 4 inputs, a couple hidden layers and 3 outputs. That is, current x, y, heading, and time as inputs and a desired x y heading as outputs.

I also finished saving an entire network. That is, the architecture, transfer funciton, and weights. I have code to load a network that compiles, but I haven't tested it yet.