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Evaluation and improvement of associative memory for pattern recognition

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Abstract

Optical systems of associative memory models are capable of reconstructing lost information from incomplete input patterns. In this paper, we evaluate the ability of associative memory models when used in practical pattern recognition systems. Effects of improvement techniques, including defocusing preprocessing, and the recursive use of the associative operation are also examined with computer simulations. Finally the effectiveness of the recognition system is tested experimentally with alphabetic characters in different illumination conditions.

© 1990 Optical Society of America

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