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dc.contributor.authorLin, Hairong
dc.contributor.authorWang, Chunhua
dc.contributor.authorSun, Yichuang
dc.contributor.authorYao, Wei
dc.date.accessioned2020-06-06T00:07:38Z
dc.date.available2020-06-06T00:07:38Z
dc.date.issued2020-06-01
dc.identifier.citationLin , H , Wang , C , Sun , Y & Yao , W 2020 , ' Firing multistability in a locally active memristive neuron model ' , Nonlinear Dynamics , vol. 100 , no. 4 , pp. 3667-3683 . https://doi.org/10.1007/s11071-020-05687-3
dc.identifier.issn0924-090X
dc.identifier.otherPURE: 21817608
dc.identifier.otherPURE UUID: 3a534b08-af34-42cb-8a56-64c76f21054f
dc.identifier.otherScopus: 85084859253
dc.identifier.urihttp://hdl.handle.net/2299/22815
dc.descriptionFunding Information: This work is supported by The Major Research Project of the National Natural Science Foundation of China (91964108), The National Natural Science Foundation of China (61971185), The Open Fund Project of Key Laboratory in Hunan Universities (18K010). Publisher Copyright: © 2020, Springer Nature B.V. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
dc.description.abstractThe theoretical, numerical and experimental demonstrations of firing dynamics in isolated neuron are of great significance for the understanding of neural function in human brain. In this paper, a new type of locally active and non-volatile memristor with three stable pinched hysteresis loops is presented. Then, a novel locally active memristive neuron model is established by using the locally active memristor as a connecting autapse, and both firing patterns and multistability in this neuronal system are investigated. We have confirmed that, on the one hand, the constructed neuron can generate multiple firing patterns like periodic bursting, periodic spiking, chaotic bursting, chaotic spiking, stochastic bursting, transient chaotic bursting and transient stochastic bursting. On the other hand, the phenomenon of firing multistability with coexisting four kinds of firing patterns can be observed via changing its initial states. It is worth noting that the proposed neuron exhibits such firing multistability previously unobserved in single neuron model. Finally, an electric neuron is designed and implemented, which is extremely useful for the practical scientific and engineering applications. The results captured from neuron hardware experiments match well with the theoretical and numerical simulation results.en
dc.format.extent17
dc.language.isoeng
dc.relation.ispartofNonlinear Dynamics
dc.rightsEmbargoed
dc.subjectFiring
dc.subjectLocally active memristor
dc.subjectMultistability
dc.subjectNeuron model
dc.subjectNeuronal circuit
dc.subjectControl and Systems Engineering
dc.subjectAerospace Engineering
dc.subjectOcean Engineering
dc.subjectMechanical Engineering
dc.subjectApplied Mathematics
dc.subjectElectrical and Electronic Engineering
dc.titleFiring multistability in a locally active memristive neuron modelen
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.embargoedUntil2021-05-19
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85084859253&partnerID=8YFLogxK
dc.relation.schoolSchool of Physics, Engineering & Computer Science
dc.description.versiontypeFinal Accepted Version
dcterms.dateAccepted2020-06-01
rioxxterms.versionAM
rioxxterms.versionofrecordhttps://doi.org/10.1007/s11071-020-05687-3
rioxxterms.licenseref.uriUnspecified
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeEmbargoed


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