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Delay-dependent exponential stability analysis of delayed cellular neural networks

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

For the delayed cellular neural networks, the estimate of exponential convergence rate and exponential stability is considered in this paper. The Lyapunov-Krasovskii functionals combined with linear matrix inequality (LMI) approach are employed to investigate the bound on the cell template and delay-type cell template matrices so that the systems are exponentially stable. Some criteria for the exponential stability which can give information on the delay-dependence are derived.
Original languageEnglish
Title of host publication2002 International Conference on Communications, Circuits and Systems and West Sino Exposition, ICCCAS 2002 - Proceedings
PublisherIEEE
Pages1657-1661
Volume2
ISBN (Print)0780375475, 9780780375475
DOIs
Publication statusPublished - 2002
Event1st International Conference on Communications, Circuits and Systems, ICCCAS 2002 - Chengdu, China
Duration: 29 Jun 20021 Jul 2002

Publication series

Name
Volume2

Conference

Conference1st International Conference on Communications, Circuits and Systems, ICCCAS 2002
PlaceChina
CityChengdu
Period29/06/021/07/02

Research Keywords

  • Cellular neural networks
  • Exponentially stability
  • Linear matrix inequality
  • Lyapunov-Krasovskii functional
  • Time delay

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