An Extended Method of SIRMs Connected Fuzzy Inference Method Using Kernel Method
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概要
- 論文の詳細を見る
The single input rule modules connected fuzzy inference method (SIRMs method) by Yubazaki et al. can decrease the number of fuzzy rules drastically in comparison with the conventional fuzzy inference methods. Moreover, Seki et al. have proposed a functional-type SIRMs method which generalizes the consequent part of the SIRMs method to function. However, these SIRMs methods can not be applied to XOR (Exclusive OR). In this paper, we propose a “kernel-type SIRMs method” which uses the kernel trick to the SIRMs method, and show that this method can treat XOR. Further, a learning algorithm of the proposed SIRMs method is derived by using the steepest descent method, and compared with the one of conventional SIRMs method and kernel perceptron by applying to identification of nonlinear functions, medical diagnostic system and discriminant analysis of Iris data.
著者
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Watanabe Satoshi
Graduate School Of Science And Technology Chiba University:japan International Research Center For A
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SEKI Hirosato
Graduate School of Information Science and Technology, Osaka University
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MIZUGUCHI Fuhito
Kronos, Inc.
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ISHII Hiroaki
Graduate School of Information Science and Technology, Osaka University
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MIZUMOTO Masaharu
Department of Engineering Informatics, Osaka Electro-Communication University
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