Delay-dependent stability analysis for recurrent neural networks with time-varying delay

C. Y. Lu, T. J. Su, S. C. Huang

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

A global stability analysis of a particular class of recurrent neural networks with time-varying delay is performed. Both Lipschitz continuous and monotone non-decreasing activation functions are considered. Globally asymptotically delay-dependent stability criteria are derived in the form of linear matrix inequalities through the use of Leibniz-Newton formula and relaxation matrices. Finally, two numerical examples are given to illustrate the effectiveness of the given criterion.

Original languageEnglish
Pages (from-to)736-742
Number of pages7
JournalIET Control Theory and Applications
Volume2
Issue number8
DOIs
Publication statusPublished - 2008 Jul 24

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Control and Optimization
  • Electrical and Electronic Engineering

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