Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/7328
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dc.contributor.authorLiu, Y-
dc.contributor.authorWang, Z-
dc.contributor.authorLiang, J-
dc.contributor.authorLiu, X-
dc.date.accessioned2013-03-25T11:36:56Z-
dc.date.available2013-03-25T11:36:56Z-
dc.date.issued2013-
dc.identifier.citationIEEE Transactions on Cybernetics, 43(1): 102 - 114, Feb 2013en_US
dc.identifier.issn2168-2267-
dc.identifier.urihttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6225448en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/7328-
dc.descriptionThis is the post-print version of the Article. The official published version can be accessed from the links below - Copyright @ 2013 IEEE.en_US
dc.description.abstractIn this paper, the synchronization problem is studied for an array of N identical delayed neutral-type neural networks with Markovian jumping parameters. The coupled networks involve both the mode-dependent discrete-time delays and the mode-dependent unbounded distributed time delays. All the network parameters including the coupling matrix are also dependent on the Markovian jumping mode. By introducing novel Lyapunov-Krasovskii functionals and using some analytical techniques, sufficient conditions are derived to guarantee that the coupled networks are asymptotically synchronized in mean square. The derived sufficient conditions are closely related with the discrete-time delays, the distributed time delays, the mode transition probability, and the coupling structure of the networks. The obtained criteria are given in terms of matrix inequalities that can be efficiently solved by employing the semidefinite program method. Numerical simulations are presented to further demonstrate the effectiveness of the proposed approach.en_US
dc.description.sponsorshipThis work was supported in part by the Royal Society of the U.K., the National Natural Science Foundation of China under Grants 61074129, 61174136 and 61134009, and the Natural Science Foundation of Jiangsu Province of China under Grants BK2010313 and BK2011598.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectArraysen_US
dc.subjectBiological neural networksen_US
dc.subjectDelayen_US
dc.subjectDelay effectsen_US
dc.subjectLinear matrix inequalitiesen_US
dc.subjectSynchronizationen_US
dc.titleSynchronization of coupled neutral-type neural networks with jumping-mode-dependent discrete and unbounded distributed delaysen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1109/TSMCB.2012.2199751-
pubs.organisational-data/Brunel-
pubs.organisational-data/Brunel/Brunel Active Staff-
pubs.organisational-data/Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths-
pubs.organisational-data/Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths/IS and Computing-
pubs.organisational-data/Brunel/University Research Centres and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Centre for Systems and Synthetic Biology-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Centre for Information and Knowledge Management-
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Computer Science
Dept of Computer Science Research Papers

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