Proceedings PaperNeural Processing Systems
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Neural processors are self-organizing Hamiltonian systems with adaptive energy functions, and are commonly referred to as "Neural Networks." They are characterized by a set of differential or difference equations, and can process information by means of their state response to initial or continuous input. Such processors consist of a large number of mutually interconnected nonlinear devices, appropriately called Processing elements or more prosaically referred to as "neurons." See references 1-3 for elaboration.