Global exponential stability for a class of retarded functional differential equations with applications in neural networks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

27 Scopus Citations
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Author(s)

  • Xiaofeng Liao
  • Kwok-Wo Wong

Detail(s)

Original languageEnglish
Pages (from-to)125-148
Journal / PublicationJournal of Mathematical Analysis and Applications
Volume293
Issue number1
Publication statusPublished - 1 May 2004

Abstract

In this paper, the global exponential stability and asymptotic stability of retarded functional differential equations with multiple time-varying delays are studied by employing several Lyapunov functionals. A number of sufficient conditions for these types of stability are presented. Our results show that these conditions are milder and more general than previously known criteria, and can be applied to neural networks with a broad range of activation functions assuming neither differentiability nor strict monotonicity. Furthermore, the results obtained for neural networks with time-varying delays do not assume symmetry of the connection matrix. © 2004 Published by Elsevier Inc.

Research Area(s)

  • Global asymptotic stability, Global exponential stability, Lyapunov functionals, Retarded functional differential equations, Time-varying delays