Global robust stability for delayed neural networks with polytopic type uncertainties

Yong He, Qing Guo Wang, Wei Xing Zheng

Research output: Contribution to journalArticlepeer-review

86 Citations (Scopus)

Abstract

In this paper, global robust stability for delayed neural networks is studied. First the free-weighting matrices are employed to express the relationship between the terms in the system equation, and a stability condition for delayed neural networks is derived by using the S-procedure. Then this result is extended to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. A numerical example given in [IEEE Trans Circuits Syst II 52 (2005) 33-36] for interval delayed neural networks is investigated. The effectiveness of the presented global robust stability criterion and its improvement over the existing results are demonstrated.

Original languageEnglish
Pages (from-to)1349-1354
Number of pages6
JournalChaos, Solitons and Fractals
Volume26
Issue number5
DOIs
Publication statusPublished - Dec 2005
Externally publishedYes

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • General Mathematics
  • General Physics and Astronomy
  • Applied Mathematics

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