New exponential stability results for delayed neural networks with time varying delays

YUCEL E., Arik S.

PHYSICA D-NONLINEAR PHENOMENA, vol.191, pp.314-322, 2004 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 191
  • Publication Date: 2004
  • Doi Number: 10.1016/j.physd.2003.11.010
  • Journal Name: PHYSICA D-NONLINEAR PHENOMENA
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.314-322
  • Istanbul University Affiliated: Yes

Abstract

This paper presents new sufficient conditions for the uniqueness and exponential stability of the equilibrium point for delayed neural networks with time varying delays. By employing a more general type of Lyapunov-Krasovskii functional and using LMI (linear matrix inequality), we derive new results for exponential stability of the equilibrium point for delayed neural networks. The results establish a relation between the delay time and the parameters of the network. The results are compared with the previous results derived in the literature. (C) 2003 Elsevier B.V. All rights reserved.