New stability criteria for Takagi-Sugeno fuzzy Hopfield neural networks

Research output: Contribution to journalArticle

Abstract

In this paper, new stability criteria are derived for Takagi-Sugeno (T-S) fuzzy Hopfield neural networks via the input/output-to-state stability (IOSS) approach. Based on matrix norm and linear matrix inequality (LMI), these stability criteria guarantee input/output-to-state stability for external input vector. Moreover, the criteria for asymptotic stability of T-S fuzzy Hopfield neural networks without external input vector are presented.

Original languageEnglish
Pages (from-to)237-246
Number of pages10
JournalInternational Journal of Pure and Applied Mathematics
Volume75
Issue number2
Publication statusPublished - 2012 Mar 12
Externally publishedYes

Keywords

  • Input/output-to-state stability (IOSS)
  • Linear matrix inequality (LMI)
  • Takagi-Sugeno (T-S) fuzzy Hopfield neural networks

ASJC Scopus subject areas

  • Mathematics(all)
  • Applied Mathematics

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