An LMI approach to passivity analysis for uncertain neural networks with multiple time-varying delays

Chien-Yu Lu, Chin-Wen Liao, Hsun Heng Tsai, Jason Sheng Hong Tsai, Jui Chuan Cheng

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper deals with the problem of Passivity analysis for neural networks with multiple time-varying delays subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. New passivity conditions are proposed by using Lyapunov-Krasovskii functionals and the free-weighting matrix method to relax the existing requirement of derivative of time delays of the system. Passivity conditions are obtained in terms of linear matrix inequalities, which can be investigated easily by using recently developed standard algorithms. Two illustrative examples are provided to demonstrate the effectiveness.

Original languageEnglish
Pages (from-to)307-314
Number of pages8
JournalInternational Journal of Electrical Engineering
Volume14
Issue number4
Publication statusPublished - 2007 Aug 1

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Linear matrix inequalities
Time delay
Chemical activation
Derivatives
Neural networks
Uncertainty

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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An LMI approach to passivity analysis for uncertain neural networks with multiple time-varying delays. / Lu, Chien-Yu; Liao, Chin-Wen; Tsai, Hsun Heng; Tsai, Jason Sheng Hong; Cheng, Jui Chuan.

In: International Journal of Electrical Engineering, Vol. 14, No. 4, 01.08.2007, p. 307-314.

Research output: Contribution to journalArticle

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