Idiotypic network model for feature extraction in pattern recognition - Effect of diffusion of antibody

Toshiyuki Shimooka; Koichi Shimizu

Idiotypic network model for feature extraction in pattern recognition - Effect of diffusion of antibody

Research output: Contribution to journal › Conference article

Abstract

An idiotypic network model using antibodies as partial templates was applied to a pattern recognition problem. A novel network model that contains diffusion of antibodies was proposed. The proposed technique was applied to classification of 33 samples of Chinese characters that have a common sub-structure in the character. With partial template matching they were classified into 12 groups. Using the dynamics of the proposed network, the samples were classified into 18 groups. Through this study, the applicability of the idiotypic network with antibody diffusion to pattern recognition was verified.

Original language	English
Pages (from-to)	511-518
Number of pages	8
Journal	Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume	2774 PART 2
Publication status	Published - 2003 Dec 1
Externally published	Yes
Event	7th International Conference, KES 2003 - Oxford, United Kingdom Duration: 2003 Sep 3 → 2003 Sep 5

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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Shimooka, T., & Shimizu, K. (2003). Idiotypic network model for feature extraction in pattern recognition - Effect of diffusion of antibody. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 2774 PART 2, 511-518.

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abstract = "An idiotypic network model using antibodies as partial templates was applied to a pattern recognition problem. A novel network model that contains diffusion of antibodies was proposed. The proposed technique was applied to classification of 33 samples of Chinese characters that have a common sub-structure in the character. With partial template matching they were classified into 12 groups. Using the dynamics of the proposed network, the samples were classified into 18 groups. Through this study, the applicability of the idiotypic network with antibody diffusion to pattern recognition was verified.",

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N2 - An idiotypic network model using antibodies as partial templates was applied to a pattern recognition problem. A novel network model that contains diffusion of antibodies was proposed. The proposed technique was applied to classification of 33 samples of Chinese characters that have a common sub-structure in the character. With partial template matching they were classified into 12 groups. Using the dynamics of the proposed network, the samples were classified into 18 groups. Through this study, the applicability of the idiotypic network with antibody diffusion to pattern recognition was verified.

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