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dc.contributor.authorYao, Wei
dc.contributor.authorWang, Chunhua
dc.contributor.authorSun, Yichuang
dc.contributor.authorZhou, Chao
dc.date.accessioned2020-06-17T00:44:32Z
dc.date.available2020-06-17T00:44:32Z
dc.date.issued2020-06-10
dc.identifier.citationYao , W , Wang , C , Sun , Y & Zhou , C 2020 , ' Robust Multimode Function Synchronization of Memristive Neural Networks with Parameter Perturbations and Time-Varying Delays ' , IEEE Transactions on Systems, Man, and Cybernetics: Systems , vol. 2020 , TSMC.2020.2997930 . https://doi.org/10.1109/TSMC.2020.2997930
dc.identifier.issn2168-2216
dc.identifier.otherPURE: 21589113
dc.identifier.otherPURE UUID: 118df115-e72e-4993-8c55-195c63954f61
dc.identifier.otherScopus: 85086740017
dc.identifier.urihttp://hdl.handle.net/2299/22860
dc.descriptionPublisher Copyright: IEEE Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
dc.description.abstractCurrently, some works on studying complete synchronization of dynamical systems are usually restricted to its two special cases: 1) power-rate synchronization and 2) exponential synchronization. Therefore, how to give a generalization of these types of complete synchronization by the mathematical expression is an open question that needs to be urgently solved. To begin with, this article proposes multimode function synchronization by the mathematical expression for the first time, which is a generalization of exponential synchronization, power-rate synchronization, logarithmical synchronization, and so on. Moreover, two adaptive controllers are designed to achieve robust multimode function synchronization of memristive neural networks (MNNs) with mismatched parameters and uncertain parameters. Each adaptive controller includes function r(t) and update gain σ. By choosing different types of r(t), multiple types of complete synchronization, including power-rate synchronization and exponential synchronization can be obtained. And update gain σ can be used to adjust the speed of synchronization. Therefore, our results enlarge and strengthen the existing results. Two examples are put forward to verify the validity of our results.en
dc.format.extent15
dc.language.isoeng
dc.relation.ispartofIEEE Transactions on Systems, Man, and Cybernetics: Systems
dc.rightsOpen
dc.subjectAdaptive controller
dc.subjectConvergence
dc.subjectDelays
dc.subjectDynamical systems
dc.subjectFeedback control
dc.subjectMulti-layer neural network
dc.subjectPerturbation methods
dc.subjectSynchronization
dc.subjectcomplete synchronization
dc.subjectmemristive neural networks (MNNs)
dc.subjectmismatched parameters
dc.subjectmultimode function synchronization
dc.subjectuncertain parameters
dc.subjectSoftware
dc.subjectControl and Systems Engineering
dc.subjectHuman-Computer Interaction
dc.subjectComputer Science Applications
dc.subjectElectrical and Electronic Engineering
dc.titleRobust Multimode Function Synchronization of Memristive Neural Networks with Parameter Perturbations and Time-Varying Delaysen
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.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85086740017&partnerID=8YFLogxK
dc.relation.schoolSchool of Physics, Engineering & Computer Science
dc.description.versiontypeFinal Accepted Version
dcterms.dateAccepted2020-06-10
rioxxterms.versionAM
rioxxterms.versionofrecordhttps://doi.org/10.1109/TSMC.2020.2997930
rioxxterms.licenseref.uriUnspecified
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


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