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dc.contributor.authorYao, Wei
dc.contributor.authorWang, Chunhua
dc.contributor.authorSun, Yichuang
dc.contributor.authorGong, Shuqing
dc.contributor.authorLin, Hairong
dc.date.accessioned2023-07-03T10:15:02Z
dc.date.available2023-07-03T10:15:02Z
dc.date.issued2023-05-04
dc.identifier.citationYao , W , Wang , C , Sun , Y , Gong , S & Lin , H 2023 , ' Event-Triggered Control for Robust Exponential Synchronization of Inertial Memristive Neural Networks Under Parameter Disturbance ' , Neural Networks , vol. 164 , pp. 67-80 . https://doi.org/10.1016/j.neunet.2023.04.024
dc.identifier.issn0893-6080
dc.identifier.urihttp://hdl.handle.net/2299/26456
dc.description© 2023 Elsevier Ltd. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.neunet.2023.04.024
dc.description.abstractSynchronization of memristive neural networks (MNNs) by using network control scheme has been widely and deeply studied. However, these researches are usually restricted to traditional continuous-time control methods for synchronization of the first-order MNNs. In this paper, we study the robust exponential synchronization of inertial memristive neural networks (IMNNs) with time-varying delays and parameter disturbance via event-triggered control (ETC) scheme. First, the delayed IMNNs with parameter disturbance are changed into first-order MNNs with parameter disturbance by constructing proper variable substitutions. Next, a kind of state feedback controller is designed to the response IMNN with parameter disturbance. Based on feedback controller, some ETC methods are provided to largely decrease the update times of controller. Then, some sufficient conditions are provided to realize robust exponential synchronization of delayed IMNNs with parameter disturbance via ETC scheme. Moreover, the Zeno behavior will not happen in all ETC conditions shown in this paper. Finally, numerical simulations are given to verify the advantages of the obtained results such as anti-interference performance and good reliability.en
dc.format.extent14
dc.format.extent830670
dc.language.isoeng
dc.relation.ispartofNeural Networks
dc.subjectEvent-triggered control
dc.subjectInertial memristive neural networks
dc.subjectParameter disturbance
dc.subjectRobust exponential synchronization
dc.subjectCognitive Neuroscience
dc.subjectArtificial Intelligence
dc.titleEvent-Triggered Control for Robust Exponential Synchronization of Inertial Memristive Neural Networks Under Parameter Disturbanceen
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Engineering and Technology
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionCentre for Future Societies Research
dc.contributor.institutionCommunications and Intelligent Systems
dc.description.statusPeer reviewed
dc.date.embargoedUntil2025-04-26
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85162048058&partnerID=8YFLogxK
rioxxterms.versionofrecord10.1016/j.neunet.2023.04.024
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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