Global exponential stability of hybrid bidirectional associative memory neural networks with discrete delays

Xiaofeng Liao, Kwok-Wo Wong

    Research output: Journal Publications and ReviewsRGC 22 - Publication in policy or professional journal

    38 Citations (Scopus)
    15 Downloads (CityUHK Scholars)

    Abstract

    The investigation of the dynamical characteristics of hybrid bidirectional associative memory (BAM) neural networks was done with constant transmission delays. A set of easily verifiable delay-independent sufficient conditions for the hybrid BAM with delays to converge exponentially to the equilibria associated with temporally uniform external inputs introduced from outside the network was also obtained by using Halanay-type inequalities. The existence and exponential stability of the unique equilibrium of hybrid BAM neural networks was also investigated.
    Original languageEnglish
    Article number42901
    Pages (from-to)429011-429014
    JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
    Volume67
    Issue number4 1
    DOIs
    Publication statusPublished - Apr 2003

    Publisher's Copyright Statement

    • COPYRIGHT TERMS OF DEPOSITED FINAL PUBLISHED VERSION FILE: Liao, X., & Wong, K-W. (2003). Global exponential stability of hybrid bidirectional associative memory neural networks with discrete delays. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 67(4 1), 429011-429014. [42901]. https://doi.org/10.1103/PhysRevE.67.042901. The copyright of this article is owned by American Physical Society.

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