On the application of a diffusive memristor compact model to neuromorphic circuits

Autores
Ferri, Agustín Cisternas; Rapoport, Alan; Fierens, Pablo Ignacio; Patterson, Germán Agustín; Miranda, Enrique; Suñé, Jordi
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Memristive devices have found application in both random access memory and neuromorphic circuits. In particular, it is known that their behavior resembles that of neuronal synapses. However, it is not simple to come by samples of memristors and adjusting their parameters to change their response requires a laborious fabrication process. Moreover, sample to sample variability makes experimentation with memristor-based synapses even harder. The usual alternatives are to either simulate or emulate the memristive systems under study. Both methodologies require the use of accurate modeling equations. In this paper, we present a diffusive compact model of memristive behavior that has already been experimentally validated. Furthermore, we implement an emulation architecture that enables us to freely explore the synapse-like characteristics of memristors. The main advantage of emulation over simulation is that the former allows us to work with real-world circuits. Our results can give some insight into the desirable characteristics of the memristors for neuromorphic applications.
Fil: Ferri, Agustín Cisternas. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Rapoport, Alan. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Fierens, Pablo Ignacio. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Patterson, Germán Agustín. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Miranda, Enrique. Universitat Autònoma de Barcelona; España
Fil: Suñé, Jordi. Universitat Autònoma de Barcelona; España
Materia
COMPACT MODEL
EMULATOR
MEMRISTOR
NEUROMORPHIC
PAVLOV
STDP
SYNAPSE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/123160
Acceder
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network_name_str CONICET Digital (CONICET)
spelling On the application of a diffusive memristor compact model to neuromorphic circuitsFerri, Agustín CisternasRapoport, AlanFierens, Pablo IgnacioPatterson, Germán AgustínMiranda, EnriqueSuñé, JordiCOMPACT MODELEMULATORMEMRISTORNEUROMORPHICPAVLOVSTDPSYNAPSEhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1https://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Memristive devices have found application in both random access memory and neuromorphic circuits. In particular, it is known that their behavior resembles that of neuronal synapses. However, it is not simple to come by samples of memristors and adjusting their parameters to change their response requires a laborious fabrication process. Moreover, sample to sample variability makes experimentation with memristor-based synapses even harder. The usual alternatives are to either simulate or emulate the memristive systems under study. Both methodologies require the use of accurate modeling equations. In this paper, we present a diffusive compact model of memristive behavior that has already been experimentally validated. Furthermore, we implement an emulation architecture that enables us to freely explore the synapse-like characteristics of memristors. The main advantage of emulation over simulation is that the former allows us to work with real-world circuits. Our results can give some insight into the desirable characteristics of the memristors for neuromorphic applications.Fil: Ferri, Agustín Cisternas. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Rapoport, Alan. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Fierens, Pablo Ignacio. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Patterson, Germán Agustín. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Miranda, Enrique. Universitat Autònoma de Barcelona; EspañaFil: Suñé, Jordi. Universitat Autònoma de Barcelona; EspañaMultidisciplinary Digital Publishing Institute2019-07-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/123160Ferri, Agustín Cisternas; Rapoport, Alan; Fierens, Pablo Ignacio; Patterson, Germán Agustín; Miranda, Enrique; et al.; On the application of a diffusive memristor compact model to neuromorphic circuits; Multidisciplinary Digital Publishing Institute; Materials; 12; 14; 13-7-2019; 1-181996-1944CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1996-1944/12/14/2260info:eu-repo/semantics/altIdentifier/doi/10.3390/ma12142260info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:26:51Zoai:ri.conicet.gov.ar:11336/123160instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:26:51.902CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv On the application of a diffusive memristor compact model to neuromorphic circuits
title On the application of a diffusive memristor compact model to neuromorphic circuits
spellingShingle On the application of a diffusive memristor compact model to neuromorphic circuits
Ferri, Agustín Cisternas
COMPACT MODEL
EMULATOR
MEMRISTOR
NEUROMORPHIC
PAVLOV
STDP
SYNAPSE
title_short On the application of a diffusive memristor compact model to neuromorphic circuits
title_full On the application of a diffusive memristor compact model to neuromorphic circuits
title_fullStr On the application of a diffusive memristor compact model to neuromorphic circuits
title_full_unstemmed On the application of a diffusive memristor compact model to neuromorphic circuits
title_sort On the application of a diffusive memristor compact model to neuromorphic circuits
dc.creator.none.fl_str_mv Ferri, Agustín Cisternas
Rapoport, Alan
Fierens, Pablo Ignacio
Patterson, Germán Agustín
Miranda, Enrique
Suñé, Jordi
author Ferri, Agustín Cisternas
author_facet Ferri, Agustín Cisternas
Rapoport, Alan
Fierens, Pablo Ignacio
Patterson, Germán Agustín
Miranda, Enrique
Suñé, Jordi
author_role author
author2 Rapoport, Alan
Fierens, Pablo Ignacio
Patterson, Germán Agustín
Miranda, Enrique
Suñé, Jordi
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv COMPACT MODEL
EMULATOR
MEMRISTOR
NEUROMORPHIC
PAVLOV
STDP
SYNAPSE
topic COMPACT MODEL
EMULATOR
MEMRISTOR
NEUROMORPHIC
PAVLOV
STDP
SYNAPSE
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Memristive devices have found application in both random access memory and neuromorphic circuits. In particular, it is known that their behavior resembles that of neuronal synapses. However, it is not simple to come by samples of memristors and adjusting their parameters to change their response requires a laborious fabrication process. Moreover, sample to sample variability makes experimentation with memristor-based synapses even harder. The usual alternatives are to either simulate or emulate the memristive systems under study. Both methodologies require the use of accurate modeling equations. In this paper, we present a diffusive compact model of memristive behavior that has already been experimentally validated. Furthermore, we implement an emulation architecture that enables us to freely explore the synapse-like characteristics of memristors. The main advantage of emulation over simulation is that the former allows us to work with real-world circuits. Our results can give some insight into the desirable characteristics of the memristors for neuromorphic applications.
Fil: Ferri, Agustín Cisternas. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Rapoport, Alan. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Fierens, Pablo Ignacio. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Patterson, Germán Agustín. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Miranda, Enrique. Universitat Autònoma de Barcelona; España
Fil: Suñé, Jordi. Universitat Autònoma de Barcelona; España
description Memristive devices have found application in both random access memory and neuromorphic circuits. In particular, it is known that their behavior resembles that of neuronal synapses. However, it is not simple to come by samples of memristors and adjusting their parameters to change their response requires a laborious fabrication process. Moreover, sample to sample variability makes experimentation with memristor-based synapses even harder. The usual alternatives are to either simulate or emulate the memristive systems under study. Both methodologies require the use of accurate modeling equations. In this paper, we present a diffusive compact model of memristive behavior that has already been experimentally validated. Furthermore, we implement an emulation architecture that enables us to freely explore the synapse-like characteristics of memristors. The main advantage of emulation over simulation is that the former allows us to work with real-world circuits. Our results can give some insight into the desirable characteristics of the memristors for neuromorphic applications.
publishDate 2019
dc.date.none.fl_str_mv 2019-07-13
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/123160
Ferri, Agustín Cisternas; Rapoport, Alan; Fierens, Pablo Ignacio; Patterson, Germán Agustín; Miranda, Enrique; et al.; On the application of a diffusive memristor compact model to neuromorphic circuits; Multidisciplinary Digital Publishing Institute; Materials; 12; 14; 13-7-2019; 1-18
1996-1944
CONICET Digital
CONICET
url http://hdl.handle.net/11336/123160
identifier_str_mv Ferri, Agustín Cisternas; Rapoport, Alan; Fierens, Pablo Ignacio; Patterson, Germán Agustín; Miranda, Enrique; et al.; On the application of a diffusive memristor compact model to neuromorphic circuits; Multidisciplinary Digital Publishing Institute; Materials; 12; 14; 13-7-2019; 1-18
1996-1944
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1996-1944/12/14/2260
info:eu-repo/semantics/altIdentifier/doi/10.3390/ma12142260
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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