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13 October 1997 Fuzzy logic genetic algorithm for hypercompression
Tomasz P. Jannson, Andrew A. Kostrzewski, Igor V. Ternovskiy, Dai Hyun Kim
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Proceedings Volume 3165, Applications of Soft Computing; (1997) https://doi.org/10.1117/12.284216
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States
Abstract
In this presentation, a fuzzy logic adaptive genetic algorithm (FLAGA) software engine is applied to hypercompression pre- processing. The FLAGA has a genetic algorithm (GA)-engine, tunable by fuzzy-logic rules. As a result, basic GA-engine operations, such as spanning, crossover, and mutation, have tunable rates, according to progress in the convergence process. Since the rates of these operations are not fixed but optimized in real-time, FLAGA convergence speed is at least one-order-of-magnitude higher than equivalent speed for a standard GA. In this paper, we present theoretical analysis and simulation results for this specific fuzzy logic application, as well as further considerations related to the application of FLAGA to video imaging and edge-extraction ATR (automatic target recognition).
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Tomasz P. Jannson, Andrew A. Kostrzewski, Igor V. Ternovskiy, and Dai Hyun Kim "Fuzzy logic genetic algorithm for hypercompression", Proc. SPIE 3165, Applications of Soft Computing, (13 October 1997); https://doi.org/10.1117/12.284216
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KEYWORDS
Fuzzy logic
Genetic algorithms
Automatic target recognition
Computer simulations
Video
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