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On the Application of a Diffusive Memristor Compact Model to Neuromorphic Circuits.
Cisternas Ferri, Agustín; Rapoport, Alan; Fierens, Pablo I; Patterson, German A; Miranda, Enrique; Suñé, Jordi.
Afiliação
  • Cisternas Ferri A; Departamento de Física, FCEyN, UBA, Pabellón 1, Ciudad Universitaria, Buenos Aires 1428, Argentina.
  • Rapoport A; Departamento de Física, FCEyN, UBA, Pabellón 1, Ciudad Universitaria, Buenos Aires 1428, Argentina.
  • Fierens PI; Instituto Tecnológico de Buenos Aires, and National Scientific and Technical Research Council (CONICET), Buenos Aires 1437, Argentina.
  • Patterson GA; Instituto Tecnológico de Buenos Aires, and National Scientific and Technical Research Council (CONICET), Buenos Aires 1437, Argentina. gpatters@itba.edu.ar.
  • Miranda E; Departament d'Enginyeria Electrònica, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain.
  • Suñé J; Departament d'Enginyeria Electrònica, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain.
Materials (Basel) ; 12(14)2019 Jul 13.
Article em En | MEDLINE | ID: mdl-31337071
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Argentina País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Argentina País de publicação: Suíça