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New global stability criteria for interval delayed neural networks

  • Harbin Institute of Technology

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

Abstract

This paper is concerned with the problem of global robust exponential stability for a class of interval cellular neural networks with time-constant delays. By introducing a novel Lyapunov-Krasovslii functional combining with the idea of delay fractioning, some delay-dependent conditions are derived in terms of the linear matrix inequality, which guarantee the considered interval delayed cellular neural networks to be global exponentially stable. Moreover, the conservatism can be notably reduced as the the fractioning goes thinner. A numerical example is provided to demonstrate the advantage of the proposed result.

Original languageEnglish
Title of host publicationISSCAA2010 - 3rd International Symposium on Systems and Control in Aeronautics and Astronautics
Pages977-981
Number of pages5
DOIs
StatePublished - 2010
Event3rd International Symposium on Systems and Control in Aeronautics and Astronautics, ISSCAA2010 - Harbin, China
Duration: 8 Jun 201010 Jun 2010

Publication series

NameISSCAA2010 - 3rd International Symposium on Systems and Control in Aeronautics and Astronautics

Conference

Conference3rd International Symposium on Systems and Control in Aeronautics and Astronautics, ISSCAA2010
Country/TerritoryChina
CityHarbin
Period8/06/1010/06/10

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