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

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

23 Scopus Citations
View graph of relations


Related Research Unit(s)


Original languageEnglish
Pages (from-to)245-250
Journal / PublicationInternational Journal of Bifurcation and Chaos
Issue number1
Publication statusPublished - Jan 2008


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.

Research Area(s)

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