A Note on Designing Learning Rates in a Class of Neuro-Fuzzy Learning Algorithms
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概要
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In this paper, we study the problem of designing of learning rates in a class of neuro-fuzzy learning algorithms, which are widely used in recent fuzzy applications for tuning fuzzy inference rules. The analysis on the convergence of the learning algorithm in the cases of tuning parameters of fuzzy rules is conducted. Sufficient conditions for choosing appropriate learning rates have been presented such that an optimal fuzzy system model can be constructed.
- バイオメディカル・ファジィ・システム学会の論文
著者
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Shi Yan
School Of Chemistry And Chemical Engineering Southwest China Normal University
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Shi Y
School Of Information Science Kyushu Tokai University
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Mizumoto M
Faculty Of Information Science And Technology Osaka Electro-communication University
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Mizumoto Masaharu
Faculty Of Engineering Science Osaka University
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Sasaki Hirofumi
School Of Engineering Kyushu Tokai University
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