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Proceedings Paper

Fuzzy logic genetic algorithm for hypercompression
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Paper 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).

Paper Details

Date Published: 13 October 1997
PDF: 9 pages
Proc. SPIE 3165, Applications of Soft Computing, (13 October 1997); doi: 10.1117/12.284216
Show Author Affiliations
Tomasz P. Jannson, Physical Optics Corp. (United States)
Andrew A. Kostrzewski, Physical Optics Corp. (United States)
Igor V. Ternovskiy, Physical Optics Corp. (United States)
Dai Hyun Kim, Physical Optics Corp. (United States)

Published in SPIE Proceedings Vol. 3165:
Applications of Soft Computing
Bruno Bosacchi; James C. Bezdek; David B. Fogel, Editor(s)

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