Mean square exponential stability of uncertain stochastic hopfield neural networks with interval time-varying delays

Jiqing Qiu*, Hongjiu Yang, Yuanqing Xia, Jinhui Zhang

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

The problem of mean square exponential stability of uncertain stochastic Hopfield neural networks with interval time-varying delays is investigated in this paper. The delay factor is assumed to be timevarying and belongs to a given interval, which means that the derivative of the delay function can exceed one. The uncertainties considered in this paper are norm-bounded and possibly time-varying. By LyapunovKrasovskii functional approach and stochastic analysis approach, a new delay-dependent stability criteria for the exponential stability of stochastic Hopfield neural networks is derived in terms of linear matrix inequalities(LMIs). A simulation example is given to demonstrate the effectiveness of the developed techniques.

Original languageEnglish
Title of host publicationAdvanced Intelligent Computing Theories and Applications
Subtitle of host publicationWith Aspects of Artificial Intelligence - Third International Conference on Intelligent Computing, ICIC 2007, Proceedings
PublisherSpringer Verlag
Pages110-119
Number of pages10
ISBN (Print)9783540742012
DOIs
Publication statusPublished - 2007
Event3rd International Conference on Intelligent Computing, ICIC 2007 - Qingdao, China
Duration: 21 Aug 200724 Aug 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4682 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Intelligent Computing, ICIC 2007
Country/TerritoryChina
CityQingdao
Period21/08/0724/08/07

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