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Removed the eval calls from feedforward, backprop & momentum
for speed.

Implemented fahlman constant. This eliminates the 'flat spot'
problem, and gets the network to converge more reliably. XOR
seems to never get stuck with this set to 0.1. as a bonus, its 
also about 50% faster (do you sense a theme developing here?)

Removed momentum module (well, removed backprop module and 
renamed momentum module in fact). There were few code differences
and its easier to maintain this way. Default option is vanilla
backprop, momentum & fahlman adjustments are only implemented if
specified in the network config.

Bundled all the maths functions into AI::NNFlex::Mathlib

Implemented calls to error transformation function, as per
Fahlman. Testing, it doesn't seem to make much difference, but
at least now the facility is there.