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dc.contributor.authorYao, Wei
dc.contributor.authorWang, Chunhua
dc.contributor.authorCao, Jinde
dc.contributor.authorSun, Yichuang
dc.contributor.authorZhou, Chao
dc.date.accessioned2019-08-07T01:40:58Z
dc.date.available2019-08-07T01:40:58Z
dc.date.issued2019-10-21
dc.identifier.citationYao , W , Wang , C , Cao , J , Sun , Y & Zhou , C 2019 , ' Hybrid multisynchronization of coupled multistable memristive neural networks with time delays ' , Neurocomputing , vol. 363 , pp. 281-294 . https://doi.org/10.1016/j.neucom.2019.07.014
dc.identifier.issn0925-2312
dc.identifier.urihttp://hdl.handle.net/2299/21561
dc.description.abstractIn this paper, we focus on synchronization issue of coupled multistable memristive neural networks (CMMNNs) with time delay under multiple stable equilibrium states. First, we build delayed CMMNNs consisting of one master subnetwork without controller and N−1 identical slave subnetworks with controllers, and every subnetwork has n nodes. Moreover, this paper investigates multistability of delayed CMMNNs with continuous nonmonotonic piecewise linear activation function (PLAF) owning 2r+2 corner points. By using the theorems of differential inclusion and fixed point, sufficient conditions are derived such that master subnetwork of CMMNNs can acquire (r+2)n exponentially stable equilibrium points, stable periodic orbits or hybrid stable equilibrium states. Then, this paper proposes hybrid multisynchronization of delayed CMMNNs related with various external inputs under multiple stable equilibrium states for the first time. There exist (r+2)n hybrid multisynchronization manifolds in CMMNNs with different initial conditions and external inputs. Finally, two numerical simulations are given to illustrate the effectiveness of the obtained results.en
dc.format.extent14
dc.format.extent1127700
dc.language.isoeng
dc.relation.ispartofNeurocomputing
dc.subjectController
dc.subjectExternal inputs
dc.subjectHybrid multisynchronization
dc.subjectMemristive neural networks
dc.subjectMultistability
dc.subjectComputer Science Applications
dc.subjectCognitive Neuroscience
dc.subjectArtificial Intelligence
dc.titleHybrid multisynchronization of coupled multistable memristive neural networks with time delaysen
dc.contributor.institutionCommunications and Intelligent Systems
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Engineering and Technology
dc.description.statusPeer reviewed
dc.date.embargoedUntil2020-07-19
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85069663934&partnerID=8YFLogxK
rioxxterms.versionofrecord10.1016/j.neucom.2019.07.014
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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