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dc.contributor.authorYao, Wei
dc.contributor.authorWang, Chunhua
dc.contributor.authorSun, Yichuang
dc.contributor.authorZhou, Chao
dc.contributor.authorLin, Hairong
dc.date.accessioned2020-05-14T00:21:43Z
dc.date.available2020-05-14T00:21:43Z
dc.date.issued2020-09-03
dc.identifier.citationYao , W , Wang , C , Sun , Y , Zhou , C & Lin , H 2020 , ' Synchronization of inertial memristive neural networks with time-varying delays via static or dynamic event-triggered control ' , Neurocomputing , vol. 404 , pp. 367-380 . https://doi.org/10.1016/j.neucom.2020.04.099
dc.identifier.issn0925-2312
dc.identifier.otherPURE: 21240569
dc.identifier.otherPURE UUID: c7e44a32-06f4-463f-90ed-5056974f510b
dc.identifier.otherScopus: 85085237770
dc.identifier.urihttp://hdl.handle.net/2299/22696
dc.descriptionFunding Information: This work was supported in part by the National Natural Science Foundation of China under Grant 61971185, the Major Research Project of the National Natural Science Foundation of China under Grant 91964108 and the Open Fund Project of Key Laboratory in Hunan Universities under Grant 18K010. Publisher Copyright: © 2020 Elsevier B.V.
dc.description.abstractThis paper investigates the synchronization problem of inertial memristive neural networks (IMNNs) with time-varying delays via event-triggered control (ETC) scheme and state feedback controller for the first time. First, two types of state feedback controllers are designed; the first type of controller is added to the transformational first-order system, and the second type of controller is added to the original second-order system. Next, based on each feedback controller, static event-triggered control (SETC) condition and dynamic event-triggered control (DETC) condition are presented to significantly reduce the update times of controller and decrease the computing cost. Then, some sufficient conditions are given such that synchronization of IMNNs with time-varying delays can be achieved under ETC schemes. Finally, a numerical simulation and some data analyses are given to verify the validity of the proposed results.en
dc.format.extent14
dc.language.isoeng
dc.relation.ispartofNeurocomputing
dc.subjectEvent-triggered control
dc.subjectInertial memristive neural networks
dc.subjectState feedback controllers
dc.subjectSynchronization
dc.subjectComputer Science Applications
dc.subjectCognitive Neuroscience
dc.subjectArtificial Intelligence
dc.titleSynchronization of inertial memristive neural networks with time-varying delays via static or dynamic event-triggered controlen
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionCommunications and Intelligent Systems
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Engineering and Technology
dc.description.statusPeer reviewed
dc.date.embargoedUntil2021-05-08
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85085237770&partnerID=8YFLogxK
rioxxterms.versionAM
rioxxterms.versionofrecordhttps://doi.org/10.1016/j.neucom.2020.04.099
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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