H∞ stability conditions for fuzzy neural networks

Choon Ki Ahn

doi:10.1155/2012/281821

H∞ stability conditions for fuzzy neural networks

Choon Ki Ahn

Research output: Contribution to journal › Article › peer-review

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Abstract

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

Original language	English
Article number	281821
Journal	Advances in Fuzzy Systems
DOIs	https://doi.org/10.1155/2012/281821
Publication status	Published - 2012
Externally published	Yes

ASJC Scopus subject areas

Control and Systems Engineering
Control and Optimization
Computational Mathematics

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

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

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DO - 10.1155/2012/281821

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JO - Advances in Fuzzy Systems

JF - Advances in Fuzzy Systems

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ER -

H∞ stability conditions for fuzzy neural networks

Abstract

ASJC Scopus subject areas

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