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Proceedings Paper

Neural Processing Systems
Author(s): Bill Miceli
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Paper Abstract

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.

Paper Details

Date Published: 13 February 1986
PDF: 3 pages
Proc. SPIE 0634, Optical and Hybrid Computing, (13 February 1986); doi: 10.1117/12.964023
Show Author Affiliations
Bill Miceli, ONR (United States)


Published in SPIE Proceedings Vol. 0634:
Optical and Hybrid Computing
Harold H. Szu, Editor(s)

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