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The Kernel-Based Pattern Recognition System Designed by Genetic Algorithms

Moritoshi YASUNAGA, Taro NAKAMURA, Ikuo YOSHIHARA, Jung Hwan KIM

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Summary :

We propose the kernel-based pattern recognition hardware and its design methodology using the genetic algorithm. In the proposed design methodology, pattern data are transformed into the truth tables and the truth tables are evolved to represent kernels in the discrimination functions for pattern recognition. The evolved truth tables are then synthesized to logic circuits. Because of this data direct implementation approach, no floating point numerical circuits are required and the intrinsic parallelism in the pattern data set is embedded into the circuits. Consequently, high speed recognition systems can be realized with acceptable small circuit size. We have applied this methodology to the image recognition and the sonar spectrum recognition tasks, and implemented them onto the newly developed FPGA-based reconfigurable pattern recognition board. The developed system demonstrates higher recognition accuracy and much faster processing speed than the conventional approaches.

Publication
IEICE TRANSACTIONS on Information Vol.E84-D No.11 pp.1528-1539
Publication Date
2001/11/01
Publicized
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DOI
Type of Manuscript
Special Section PAPER (Special Issue on Function Integrated Information Systems)
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