Please use this identifier to cite or link to this item: https://doi.org/10.1109/TENCON.2005.301253
DC FieldValue
dc.titleRobust stability analysis of delayed neural networks with polytopic type uncertainties
dc.contributor.authorHe, Y.
dc.contributor.authorWang, Q.-G.
dc.contributor.authorZheng, W.X.
dc.date.accessioned2014-06-19T03:26:39Z
dc.date.available2014-06-19T03:26:39Z
dc.date.issued2007
dc.identifier.citationHe, Y.,Wang, Q.-G.,Zheng, W.X. (2007). Robust stability analysis of delayed neural networks with polytopic type uncertainties. IEEE Region 10 Annual International Conference, Proceedings/TENCON 2007 : -. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/TENCON.2005.301253" target="_blank">https://doi.org/10.1109/TENCON.2005.301253</a>
dc.identifier.isbn0780393112
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/71690
dc.description.abstractWe investigate the problem of global robust stability for delayed neural networks in this paper. We first utilize the free-weighting matrices to express the relationship between the terms in the system equation, and then apply the S-procedure to derive a stability condition for delayed neural networks. Next, we extend this result so as to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. Finally, we demonstrate the usefulness of the obtained global robust stability criterion and its improvement over the existing results by using a numerical example given in [21] for interval delayed neural networks.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TENCON.2005.301253
dc.sourceScopus
dc.subjectDelayed neural networks
dc.subjectGlobal robust stability
dc.subjectLinear matrix inequality (LMI)
dc.subjectParameter-dependent Lyapunov functional
dc.subjectPolytopic type uncertainties
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/TENCON.2005.301253
dc.description.sourcetitleIEEE Region 10 Annual International Conference, Proceedings/TENCON
dc.description.volume2007
dc.description.page-
dc.description.coden85QXA
dc.identifier.isiutNOT_IN_WOS
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