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Optical neural network with bipolar neural states

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Abstract

A method to achieve bipolar performance in a single-channel optical associative memory is presented. By coding the biased interconnection weights, a distributed background, and an input-dependent dynamic threshold on a single mask, we construct an optical network with both bipolar neural states and bipolar interconnections. Content addressability and other properties are improved by the introduction of a distributed background, as compared with the case in which this background is not used. Computer simulations and optical experiments are performed based on the Hopfield algorithm.

© 1992 Optical Society of America

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