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Generation of Pattern Classifiers Based on Linear Nongroup CA
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 Title & Authors
Generation of Pattern Classifiers Based on Linear Nongroup CA
Choi, Un-Sook; Cho, Sung-Jin; Kim, Han-Doo;
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 Abstract
Nongroup Cellular Automata(CA) having two trees in the state transition diagram of a CA is suitable for pattern classifier which divides pattern set into two classes. Maji et al. [1] classified patterns by using multiple attractor cellular automata as a pattern classifier with dependency vector. In this paper we propose a method of generation of a pattern classifier using feature vector which is the extension of dependency vector. In addition, we propose methods for finding nonreachable states in the 0-tree of the state transition diagram of TPMACA corresponding to the given feature vector for the analysis of the state transition behavior of the generated pattern classifier.
 Keywords
Pattern Classifier;Cellular Automata(CA);Multiple Attractor CA(MACA);Nonreachable state;Feature Vector;
 Language
English
 Cited by
 References
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