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    Global exponential stability of impulsive discrete-time neural networks with time-varying delays

    153370_153370.pdf (171.1Kb)
    Access Status
    Open access
    Authors
    Xu, Honglei
    Chen, Y.
    Teo, Kok Lay
    Date
    2010
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Xu, Honglei and Chen, Yuanqiang and Teo, Kok Lay. 2010. Global exponential stability of impulsive discrete-time neural networks with time-varying delays. Applied Mathematics and Computations. 217 (2): pp. 537-544.
    Source Title
    Applied Mathematics and Computations
    DOI
    10.1016/j.amc.2010.05.087
    ISSN
    00963003
    School
    Department of Mathematics and Statistics
    Remarks

    NOTICE: This is the author’s version of a work that was accepted for publication in Applied Mathematics and Computation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Applied Mathematics and Computation [217, 2, 2010] DOI 10.1016/j.amc.2010.05.087

    URI
    http://hdl.handle.net/20.500.11937/16829
    Collection
    • Curtin Research Publications
    Abstract

    This paper studies the problem of global exponential stability and exponential convergence rate for a class of impulsive discrete-time neural networks with time-varying delays. Firstly, by means of the Lyapunov stability theory, some inequality analysis techniques and a discrete-time Halanay-type inequality technique, sufficient conditions for ensuring global exponential stability of discrete-time neural networks are derived, and the estimated exponential convergence rate is provided as well. The obtained results are then applied to derive global exponential stability criteria and exponential convergence rate of impulsive discrete-time neural networks with time-varying delays. Finally, numerical examples are provided to illustrate the effectiveness and usefulness of the obtained criteria.

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