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Evaluation of the computational capabilities of a memristive random network (MN3) under the context of reservoir computing.
Suarez, Laura E; Kendall, Jack D; Nino, Juan C.
Afiliación
  • Suarez LE; Department of Industrial Engineering, Universidad de los Andes, Bogotá, Colombia; Department of Materials Science and Engineering, University of Florida, Gainesville, FL 32601, USA. Electronic address: laura.suarez@mail.mcgill.ca.
  • Kendall JD; Department of Materials Science and Engineering, University of Florida, Gainesville, FL 32601, USA. Electronic address: jackdkendall@ufl.edu.
  • Nino JC; Department of Materials Science and Engineering, University of Florida, Gainesville, FL 32601, USA. Electronic address: jnino@mse.ufl.edu.
Neural Netw ; 106: 223-236, 2018 Oct.
Article en En | MEDLINE | ID: mdl-30077960
This work presents the simulation results of a novel recurrent, memristive neuromorphic architecture, the MN3 and explores its computational capabilities in the performance of a temporal pattern recognition task by considering the principles of the reservoir computing approach. A simple methodology based on the definitions of ordered and chaotic dynamical systems was used to determine the separation and fading memory properties of the architecture. The results show the potential use of this architecture as a reservoir for the on-line processing of time-varying inputs.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Redes Neurales de la Computación / Software de Reconocimiento del Habla Tipo de estudio: Clinical_trials / Evaluation_studies Idioma: En Revista: Neural Netw Asunto de la revista: NEUROLOGIA Año: 2018 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Redes Neurales de la Computación / Software de Reconocimiento del Habla Tipo de estudio: Clinical_trials / Evaluation_studies Idioma: En Revista: Neural Netw Asunto de la revista: NEUROLOGIA Año: 2018 Tipo del documento: Article Pais de publicación: Estados Unidos