H∞ stability conditions for fuzzy neural networks

Research output: Contribution to journalArticle

1 Citation (Scopus)

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 languageEnglish
Article number281821
JournalAdvances in Fuzzy Systems
DOIs
Publication statusPublished - 2012 Mar 21
Externally publishedYes

Fingerprint

Fuzzy neural networks
Fuzzy Neural Network
Stability Condition
Asymptotic stability
Linear matrix inequalities
Asymptotic Stability
Matrix Inequality
Linear Inequalities

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Mathematics
  • Control and Optimization

Cite this

H∞ stability conditions for fuzzy neural networks. / Ahn, Choon Ki.

In: Advances in Fuzzy Systems, 21.03.2012.

Research output: Contribution to journalArticle

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