Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/23555
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dc.contributor.authorZhao, Z-
dc.contributor.authorWang, Z-
dc.contributor.authorZou, L-
dc.contributor.authorGuo, G-
dc.date.accessioned2021-11-19T13:33:49Z-
dc.date.available2021-11-19T13:33:49Z-
dc.date.issued2018-10-29-
dc.identifier.citationZhao, Z., Wang, Z., Zou, L. and Guo, G. (2021) 'Finite-Time State Estimation for Delayed Neural Networks with Redundant Delayed Channels', IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51 (1), pp. 441 - 451. doi: 10.1109/TSMC.2018.2874508.en_US
dc.identifier.issn2168-2216-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/23555-
dc.description.sponsorship10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61703245 and 61873148); 10.13039/501100010029-Taishan Scholar Project of Shandong Province of China; 10.13039/501100002858-China Post-Doctoral Science Foundation (Grant Number: 2016M600547); Qingdao Post-Doctoral Applied Research Project (Grant Number: 2016117); Post-Doctoral Special Innovation Foundation of Shandong (Grant Number: 201701015); 10.13039/501100000288-Royal Society of the U.K.; 10.13039/100005156-Alexander von Humboldt Foundation of Germanyen_US
dc.format.extent441 - 451-
dc.format.mediumPrint-Electronic-
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectdelayed neural networksen_US
dc.subjectredundant delayed channelsen_US
dc.subjectstate estimationen_US
dc.subjectfinite-time boundednessen_US
dc.titleFinite-Time State Estimation for Delayed Neural Networks with Redundant Delayed Channelsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1109/TSMC.2018.2874508-
dc.relation.isPartOfIEEE Transactions on Systems, Man, and Cybernetics: Systems-
pubs.issue1-
pubs.publication-statusPublished-
pubs.volume51-
dc.identifier.eissn2168-2232-
Appears in Collections:Dept of Computer Science Research Papers

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