Global robust stability for delayed neural networks with polytopic type uncertainties

Yong He, Qing-Guo Wang, Wei Xing Zheng

    Research output: Contribution to journalArticle

    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
    JournalChaos\, Solitons & Fractals
    Publication statusPublished - 2005

    Keywords

    • global robust stability
    • matrices
    • neural networks, foundations to applications

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