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Iterative optimization algorithms for filter generation in optical correlators: a comparison

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Abstract

A general approach to the implementation of highly selective spatial filters for pattern recognition leads to a nonlinear optimization problem. Three optimization algorithms, hill climbing (direct search), simulated annealing, and the genetic algorithm, were investigated for implementation on hybrid electro-optical systems. Experimental results indicate the substantial superiority of the genetic algorithm in terms of operating speed and performance quality.

© 1992 Optical Society of America

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