Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.chaos.2005.04.005
DC FieldValue
dc.titleGlobal robust stability for delayed neural networks with polytopic type uncertainties
dc.contributor.authorHe, Y.
dc.contributor.authorWang, Q.-G.
dc.contributor.authorZheng, W.-X.
dc.date.accessioned2014-06-17T02:51:18Z
dc.date.available2014-06-17T02:51:18Z
dc.date.issued2005-12
dc.identifier.citationHe, Y., Wang, Q.-G., Zheng, W.-X. (2005-12). Global robust stability for delayed neural networks with polytopic type uncertainties. Chaos, Solitons and Fractals 26 (5) : 1349-1354. ScholarBank@NUS Repository. https://doi.org/10.1016/j.chaos.2005.04.005
dc.identifier.issn09600779
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/56151
dc.description.abstractIn 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. © 2005 Elsevier Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.chaos.2005.04.005
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1016/j.chaos.2005.04.005
dc.description.sourcetitleChaos, Solitons and Fractals
dc.description.volume26
dc.description.issue5
dc.description.page1349-1354
dc.description.codenCSFOE
dc.identifier.isiut000230330800010
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