A delay-dependent approach to passivity analysis for uncertain neural networks with time-varying Delayd

Chien-Yu Lu, Hsun Heng Tsai, Te Jen Su, Jason Sheng Hong Tsai, Chin-Wen Liao

Research output: Contribution to journalArticle

47 Citations (Scopus)

Abstract

This paper deals with the problem of passivity analysis for neural networks with time-varying delay, which is subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. Delay-dependent passivity condition is proposed by using the free-weighting matrix approach. These passivity conditions are obtained in terms of linear matrix inequalities, which can be investigated easily by using standard algorithms. Two illustrative examples are provided to demonstrate the effectiveness of the proposed criteria.

Original languageEnglish
Pages (from-to)237-246
Number of pages10
JournalNeural Processing Letters
Volume27
Issue number3
DOIs
Publication statusPublished - 2008 Jun 1

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Linear matrix inequalities
Chemical activation
Neural networks
Uncertainty

All Science Journal Classification (ASJC) codes

  • Software
  • Neuroscience(all)
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

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A delay-dependent approach to passivity analysis for uncertain neural networks with time-varying Delayd. / Lu, Chien-Yu; Tsai, Hsun Heng; Su, Te Jen; Tsai, Jason Sheng Hong; Liao, Chin-Wen.

In: Neural Processing Letters, Vol. 27, No. 3, 01.06.2008, p. 237-246.

Research output: Contribution to journalArticle

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