New global asymptotic stability criterion for uncertain neural networks with time-varying and distributed delays

Jiqing Qiu*, Jinhui Zhang, Zhifeng Gao, Hongjiu Yang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper investigates the problem of global asymptoticstability for a class of uncertain neural networks with time-varying and distributed delays. The uncertainties we considered in this paper are norm-bounded, and possibly time-varying. By Lyapunov-Krasovskii functional approach and S-procedure, a new stability criteria for the asymptotic stability of the system is derived in terms of linear matrix inequalities (LMIs). Two simulation examples are given to demonstrate the effectiveness of the developed techniques.

Original languageEnglish
Title of host publicationAdvances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
PublisherSpringer Verlag
Pages871-878
Number of pages8
EditionPART 1
ISBN (Print)9783540723820
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China
Duration: 3 Jun 20077 Jun 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4491 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Symposium on Neural Networks, ISNN 2007
Country/TerritoryChina
CityNanjing
Period3/06/077/06/07

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