Well, I'm implementing some functionality in my neural net at the moment to let it recognize gestures, since I've already finished the network I suppose I could have some tips at hand.
Representation of the gestures is pretty inituitive. Throw in an array of x & y delta's ( x(n-1) - x(n), not plain coordinates!), tell the network wich pattern you're throwing at him, and the network will eventually recognize the patterns. While I've not tested this with true mouse-gestures, this seems to work with pre-generated patterns (with some \ alot noise added to it) so I figure it'll do just as fine with the mouse.
What Laurens said about keeping things flexible is very true. You don't want to alter your entire program just because you've figured out that you need 30 more neurons, or more layers. Some understanding of basic datastructures (linked lists etc) comes in handy here.
First get your datastructures right, after that, program the output functions for the neurons, than start with the backpropagating algorythm wich is fairly complicated if you're just starting (I myself only have vague understanding of how it works - exactly - )
Usefull read:
http://www.generation5.org/content/2002/bp.asp
If you have any specific questions about how I implemented the NN, just ask!
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