Robust stability for delayed neural networks with nonlinear perturbation

Li Xie, Tianming Liu, Jilin Liu, Weikang Gu, Stephen Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The problem of analysis of robust stability for time-delayed neural networks with nonlinear perturbation has been investigated via Lyapunov stability theory. The sufficient conditions for robust stability of neural networks with time delays have been developed. The exponential stability criterion for neural networks is also derived. The result includes the information on the state convergence degree of the neural networks. The robust stable criterion in this paper is presented in terms of linear matrix inequalities.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science
EditorsJ. Wang, X. Liao, Z. Yi
Pages203-208
Number of pages6
Volume3496
EditionI
StatePublished - 2005
EventSecond International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 - Chongqing, China
Duration: May 30 2005Jun 1 2005

Other

OtherSecond International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005
CountryChina
CityChongqing
Period5/30/056/1/05

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

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