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Delay-dependent asymptotic stability of neural networks with time-varying delays

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This paper considers the problem of stability analysis for neural networks with time-varying delays. The time-varying delays under consideration are assumed to be bounded but not necessarily differentiable. In terms of a linear matrix inequality, a delay-dependent asymptotic stability condition is developed, which ensures the existence of a unique equilibrium point and its global asymptotic stability. The proposed stability condition is easy to check and less conservative. An example is provided to show the effectiveness of the proposed condition. © 2008 World Scientific Publishing Company.
Original languageEnglish
Pages (from-to)245-250
JournalInternational Journal of Bifurcation and Chaos
Volume18
Issue number1
DOIs
Publication statusPublished - Jan 2008

Research Keywords

  • Global asymptotic stability
  • Linear matrix inequality
  • Neural networks
  • Time-varying delays

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