Exponential stability analysis for neural networks with time-varying delay

Min Wu, Fang Liu, Peng Shi, Yong He, Ryuichi Yokoyama

Research output: Contribution to journalArticle

85 Citations (Scopus)

Abstract

This correspondence paper focuses on the problem of exponential stability for neural networks with a time-varying delay. The relationship among the time-varying delay, its upper bound, and their difference is taken into account. As a result, an improved linear-matrix-inequality-based delay-dependent exponential stability criterion is obtained without ignoring any terms in the derivative of Lyapunov-Krasovskii functional. Two numerical examples are given to demonstrate its effectiveness.

Original languageEnglish
Pages (from-to)1152-1156
Number of pages5
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume38
Issue number4
DOIs
Publication statusPublished - 2008 Aug

Keywords

  • Exponential stability
  • Linear matrix inequality (LMI)
  • Neural networks
  • Time-varying delay

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence
  • Human-Computer Interaction
  • Medicine(all)

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