Passivity analysis for uncertain time-varying delayed neural networks with neutral type

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

4 Citations (Scopus)

Abstract

This paper considers the problem of robust delay-dependent Passivity analysis for time-varying delayed neural networks described by nonlinear delay differential equations of the neutral type, which is subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. Both delay-dependent and delay-independent passivity conditions are proposed by using more general Lyapunov-Krasovskii functionals. These passivity conditions are obtained in terms of linear matrix inequalities, which can be investigated easily by recently using standard algorithms. An illustrative example is provided to demonstrate the effectiveness and the reduced conservatism of the proposed method.

Original languageEnglish
Title of host publicationSecond International Conference on Innovative Computing, Information and Control, ICICIC 2007
PublisherIEEE Computer Society
ISBN (Print)0769528821, 9780769528823
DOIs
Publication statusPublished - 2007 Jan 1
Event2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007 - Kumamoto, Japan
Duration: 2007 Sep 52007 Sep 7

Publication series

NameSecond International Conference on Innovative Computing, Information and Control, ICICIC 2007

Other

Other2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007
CountryJapan
CityKumamoto
Period07-09-0507-09-07

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mechanical Engineering

Cite this

Liao, C. W., & Lu, C. Y. (2007). Passivity analysis for uncertain time-varying delayed neural networks with neutral type. In Second International Conference on Innovative Computing, Information and Control, ICICIC 2007 [4427715] (Second International Conference on Innovative Computing, Information and Control, ICICIC 2007). IEEE Computer Society. https://doi.org/10.1109/ICICIC.2007.444