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The remarkable collective computational properties of the Hopfield model for neural networks Proc. Nat. Acad. Sci. USA 79, 2554 (1982) are reviewed. These include recognition from partial input, robustness, and error-correction capability. Features of the model that make its optical implementation attractive are discussed, and specific optical implementation schemes are given.
Psaltis et al. (Fri,) studied this question.
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