M-5 uses the classic Feed Forward Back Propagation algorithm to adjust connection strengths (weights).

It uses floating point math to provide results equivalent to or surpassing those of desktop systems costing hundreds of dollars.

It can have up to eight variables on the Input layer, has three neurons in the Hidden layer and an Output neuron.