Stability Conditions for Fuzzy Neural Networks | Zendy

Choon Ki Ahn | Zendy

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Stability Conditions for Fuzzy Neural Networks

Author(s) -

Choon Ki Ahn

Publication year - 2012

Publication title -

advances in fuzzy systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.38

H-Index - 19

eISSN - 1687-711X

pISSN - 1687-7101

DOI - 10.1155/2012/281821

Subject(s) - artificial neural network , stability (learning theory) , fuzzy logic , linear matrix inequality , exponential stability , control theory (sociology) , computer science , stability conditions , mathematics , fuzzy control system , mathematical optimization , artificial intelligence , nonlinear system , physics , machine learning , control (management) , statistics , discrete time and continuous time , quantum mechanics

This paper presents a novel approach to assess the stability of fuzzy neuralnetworks. First, we propose a new condition for the ℋ∞ stability of fuzzy neuralnetworks. Second, a new ℋ∞ stability condition based on linear matrix inequality(LMI) is presented for fuzzy neural networks. These conditions also ensure asymptoticstability without external input

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