Don''t know any real good articles that focus on the mathematics .. but you really shouldn''t be looking for them anyway.

The fact at the moment is that neural nets are basically a "Black art" (to quote my NN lecturer) and all there is at present are heuristics on how to do it .. but none of them are general across all applications ..

so don''t bother looking for hard and fast rules .. for any specific application you need to test out different values and decrease rates until you hit an acceptable set. It''s just experience ..

but basically all I''ve read says that the learning rate and the momentum should be pretty small to start with, though they can be a little bigger if they decrease during training.

The point of momentum is to make sure that the network doesn''t get stuck on local minima while it''s travelling downslope, and the learning rate is to prevent the overshooting of the golbal minima once you get there.

sorry if I''ve repeated the obvious .. and good luck