Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/83091
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dc.contributor.authorLi, H.-
dc.contributor.authorGao, H.-
dc.contributor.authorShi, P.-
dc.date.issued2010-
dc.identifier.citationIEEE Transactions on Neural Networks and Learning Systems, 2010; 21(11):1842-1847-
dc.identifier.issn1045-9227-
dc.identifier.issn1941-0093-
dc.identifier.urihttp://hdl.handle.net/2440/83091-
dc.description.abstractIn this brief, the problem of passivity analysis is investigated for a class of uncertain neural networks (NNs) with both discrete and distributed time-varying delays. By constructing a novel Lyapunov functional and utilizing some advanced techniques, new delay-dependent passivity criteria are established to guarantee the passivity performance of NNs. Essentially different from the available results, when estimating the upper bound of the derivative of Lyapunov functionals, we consider and best utilize the additional useful terms about the distributed delays, which leads to less conservative results. These criteria are expressed in the form of convex optimization problems, which can be efficiently solved via standard numerical software. Numerical examples are provided to illustrate the effectiveness and less conservatism of the proposed results.-
dc.description.statementofresponsibilityHongyi Li, Huijun Gao, and Peng Shi-
dc.language.isoen-
dc.publisherIEEE-Inst Electrical Electronics Engineers Inc-
dc.rights© 2010 IEEE-
dc.subjectDistributed delays-
dc.subjectneural networks (NNs)-
dc.subjectpassivity-
dc.subjecttime-varying delays.-
dc.titleNew passivity analysis for neural networks with discrete and distributed delays-
dc.typeJournal article-
dc.identifier.doi10.1109/TNN.2010.2059039-
pubs.publication-statusPublished-
dc.identifier.orcidShi, P. [0000-0001-8218-586X]-
Appears in Collections:Aurora harvest
Electrical and Electronic Engineering publications

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