Presentation 2002/3/8
Synthesis Procedure of an Associative Memory with Genetic Algorithm
Haruhiro TAKEUCHI, Kenya JIN'NO, Haruo HIROSE,
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Abstract(in English) We propose a novel synthesis procedure of an associative memory with genetic algorithm. The associative memory consists with a discrete-time neural network whose connection coefficient takes only two value, that is ±1. In our proposed synthesis procedure, the connection coefficient matrix is regarded as a gene, and the gene is evolved by a genetic algorithm. By using an proposed fitness function that is based on association rate of desired memories from similary input patterns, the genes so that takes high evaluation value is left. Many of previous related works use auto-correlation matrix to store desired memories. Our synthesis procedure does not use auto-correlation matrix as the connection matrix. but this system generate the connection matrix resembled correlation matrix. In this article, we consider the relationship between the generated matrix and the auto-correlation matrix.
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Keyword(in English) associative memory / genetic algorithm / neural networks / correlation matrix / fitness function
Paper # NLP2001-101
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Committee NLP
Conference Date 2002/3/8(1days)
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Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Synthesis Procedure of an Associative Memory with Genetic Algorithm
Sub Title (in English)
Keyword(1) associative memory
Keyword(2) genetic algorithm
Keyword(3) neural networks
Keyword(4) correlation matrix
Keyword(5) fitness function
1st Author's Name Haruhiro TAKEUCHI
1st Author's Affiliation Department of Electrical and Electronics Engineering, Nippon Institute of Technology()
2nd Author's Name Kenya JIN'NO
2nd Author's Affiliation Department of Electrical and Electronics Engineering, Nippon Institute of Technology
3rd Author's Name Haruo HIROSE
3rd Author's Affiliation Department of Electrical and Electronics Engineering, Nippon Institute of Technology
Date 2002/3/8
Paper # NLP2001-101
Volume (vol) vol.101
Number (no) 723
Page pp.pp.-
#Pages 8
Date of Issue