A hardware-implementable algorithm for learning nonlinear functions

An algorithm is presented which allows continuous functions to be learned by a neural network using spike-based stochastic reinforcement training. The algorithm may be implemented in hardware by probabilistic random access memory (pRAM) nodes. The addition of output transformation modules which impl... View More