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dc.creatorMohan, Charanrajes
dc.creatorCamuñas Mesa, Luis Alejandroes
dc.creatorRosa Utrera, José Manuel de laes
dc.creatorSerrano Gotarredona, María Teresaes
dc.creatorLinares Barranco, Bernabées
dc.date.accessioned2021-06-28T12:47:13Z
dc.date.available2021-06-28T12:47:13Z
dc.date.issued2021-04
dc.identifier.citationMohan, C., Camuñas Mesa, L.A., Rosa Utrera, J.M.d.l., Serrano Gotarredona, M.T. y Linares Barranco, B. (2021). Implementation of binary stochastic STDP learning using chalcogenide-based memristive devices. En 2021 IEEE International Symposium on Circuits and Systems (ISCAS) Daegu, Korea (South): IEEE.
dc.identifier.isbn978-1-7281-9201-7es
dc.identifier.isbn978-1-7281-9202-4es
dc.identifier.urihttps://hdl.handle.net/11441/114905
dc.description.abstractThe emergence of nano-scale memristive devices encouraged many different research areas to exploit their use in multiple applications. One of the proposed applications was to implement synaptic connections in bio-inspired neuromorphic systems. Large-scale neuromorphic hardware platforms are being developed with increasing number of neurons and synapses, having a critical bottleneck in the online learning capabilities. Spiketiming- dependent plasticity (STDP) is a widely used learning mechanism inspired by biology which updates the synaptic weight as a function of the temporal correlation between pre- and postsynaptic spikes. In this work, we demonstrate experimentally that binary stochastic STDP learning can be obtained from a memristor when the appropriate pulses are applied at both sides of the device.es
dc.description.sponsorshipEU H2020 grant 824164 "HERMES"es
dc.description.sponsorshipEU H2020 grant 871371 "Memscales"es
dc.description.sponsorshipEU H2020 grant 871501 "NeurONN"es
dc.description.sponsorshipEU H2020 grant PCI2019-111826-2 "APROVIS3D"es
dc.description.sponsorshipEU H2020 grant 899559 "SpinAge"es
dc.description.sponsorshipMinistry of Science and Innovation (Spain) PID2019-105556GB-C31es
dc.description.sponsorshipMinistry of Science and Innovation ( Spain) PID2019-103876RB-I00 (CORDION)es
dc.description.sponsorshipMinistry of Economy and Competitivity (Spain) / FEDER TEC2015- 63884-C2-1-P (COGNET)es
dc.description.sponsorshipJunta de Andalucía (Spain) US-1260118 (Neuro-Radio)es
dc.description.sponsorshipUniversidad de Sevilla (Spain) VI PPITes
dc.formatapplication/pdfes
dc.format.extent5 p.es
dc.language.isoenges
dc.publisherIEEEes
dc.relation.ispartof2021 IEEE International Symposium on Circuits and Systems (ISCAS) (2021).
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectNeuromorphic systemses
dc.subjectSTDPes
dc.subjectMemristorses
dc.subjectStochastic learninges
dc.subjectSpiking neural networkses
dc.titleImplementation of binary stochastic STDP learning using chalcogenide-based memristive deviceses
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadoreses
dc.relation.projectIDPID2019-105556GB-C31es
dc.relation.projectIDPID2019-103876RB-I00 (CORDION)es
dc.relation.projectIDTEC2015- 63884-C2-1-P (COGNET)es
dc.relation.projectIDUS-1260118 (Neuro-Radio)es
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9401159es
dc.identifier.doi10.1109/ISCAS51556.2021.9401159es
dc.contributor.groupUniversidad de Sevilla. TIC178: Diseño y Test de Circuitos Integrados de Señal Mixtaes
idus.validador.notaPreprint. Submitted versiones
dc.eventtitle2021 IEEE International Symposium on Circuits and Systems (ISCAS)es
dc.eventinstitutionDaegu, Korea (South)es

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