Interplay of multiple synaptic plasticity features in filamentary memristive devices for neuromorphic computing.

Autor: La Barbera S; Institut of Electronic, Microelectronic and Nanoelectronic, CNRS, boulevard Poincarré CS 60069, 59652 Villeneuve d'Ascq, France., Vincent AF; Centre de Nanosciences et de Nanotechnologies, CNRS, Univ. Paris-Sud, Université Paris-Saclay, C2N - Orsay, 91405 Orsay cedex, France., Vuillaume D; Institut of Electronic, Microelectronic and Nanoelectronic, CNRS, boulevard Poincarré CS 60069, 59652 Villeneuve d'Ascq, France., Querlioz D; Centre de Nanosciences et de Nanotechnologies, CNRS, Univ. Paris-Sud, Université Paris-Saclay, C2N - Orsay, 91405 Orsay cedex, France., Alibart F; Institut of Electronic, Microelectronic and Nanoelectronic, CNRS, boulevard Poincarré CS 60069, 59652 Villeneuve d'Ascq, France.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2016 Dec 16; Vol. 6, pp. 39216. Date of Electronic Publication: 2016 Dec 16.
DOI: 10.1038/srep39216
Abstrakt: Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.
Databáze: MEDLINE
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