Added regularisation to backprop and errors.

In network, I've changed the way we randomly initialise weights to the
heuristic I told you about. I'm pretty sure there's nothing wrong with
the regularisation implementation here, although having experimented
with various decay rates, it seems to do weird things sometimes. 0.1-
0.2 seemed to be a pretty decent decay rate so I might change the
default to that. Could we add a method to all layers, that does what
the RBM thing did, you know, to visualise all the features? I think it
might make it clearer to us as to whether or not the network's learning
properly.