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dc.contributor.authorXu, Honglei
dc.contributor.authorChen, Y.
dc.contributor.authorTeo, Kok Lay
dc.date.accessioned2017-01-30T11:57:58Z
dc.date.available2017-01-30T11:57:58Z
dc.date.created2011-03-02T20:01:35Z
dc.date.issued2010
dc.identifier.citationXu, 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.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/16829
dc.identifier.doi10.1016/j.amc.2010.05.087
dc.description.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.

dc.publisherElsevier
dc.subjectExponential convergence rate
dc.subjectGlobal exponential stability
dc.subjectHalanay inequality
dc.subjectImpulsive discrete-time neural networks
dc.titleGlobal exponential stability of impulsive discrete-time neural networks with time-varying delays
dc.typeJournal Article
dcterms.source.volume217
dcterms.source.startPage537
dcterms.source.endPage544
dcterms.source.issn00963003
dcterms.source.titleApplied Mathematics and Computations
curtin.note

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

curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusOpen access


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