New stability criteria for recurrent neural networks with a time-varying delay

Hong Bing Zeng*, Shen Ping Xiao, Bin Liu

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    9 Citations (Scopus)

    Abstract

    This paper deals with the stability of static recurrent neural networks (RNNs) with a time-varying delay. An augmented Lyapunov-Krasovskii functional is employed, in which some useful terms are included. Furthermore, the relationship among the time-varying delay, its upper bound and their difference, is taken into account, and novel bounding techniques for 1 - τ(t) are employed. As a result, without ignoring any useful term in the derivative of the Lyapunov-Krasovskii functional, the resulting delay-dependent criteria show less conservative than the existing ones. Finally, a numerical example is given to demonstrate the effectiveness of the proposed methods.

    Original languageEnglish
    Pages (from-to)128-133
    Number of pages6
    JournalInternational Journal of Automation and Computing
    Volume8
    Issue number1
    DOIs
    Publication statusPublished - Feb 2011

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