Global asymptotic stability of Cohen-Grossberg neural networks with multiple discrete delays

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Abstract

The asymptotic stability is analyzed for Cohen-Grossberg neural networks with multiple discrete delays. The boundedness, differentiability or monotonicity condition is not assumed on the activation functions. The generalized Dahlquist constant approach is employed to examine the existence and uniqueness of equilibrium of the neural networks, and a novel Lyapunov functional is constructed to investigate the stability of the delayed neural networks. New general sufficient conditions are derived for the global asymptotic stability of the neural networks with multiple delays.

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
Pages47-58
Number of pages12
ISBN (Print)9783540742012
DOIs
StatePublished - 2007
Externally publishedYes
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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