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STDP and STDP Variations with Memristors for Spiking Neuromorphic Learning Systems

Opened Access STDP and STDP Variations with Memristors for Spiking Neuromorphic Learning Systems


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Autor: Indiveri, Giacomo
Linares Barranco, Bernabé
Masquelier, T.
Serrano Gotarredona, María Teresa
Prodromakis, T.
Departamento: Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores
Fecha: 2013
Publicado en: Frontiers in Neuroscience, 18
Tipo de documento: Artículo
Resumen: In this paper we review several ways of realizing asynchronous Spike-Timing-DependentPlasticity (STDP) using memristors as synapses. Our focus is on how to use individual memristors to implement synaptic weight multiplications, in a way such that it is not necessary to (a) introduce global synchronization and (b) to separate memristor learning phases from memristor performing phases. In the approaches described, neurons fire spikes asynchronously when they wish and memristive synapses perform computation and learn at their own pace, as it happens in biological neural systems. We distinguish between two different memristor physics, depending on whether they respond to the original “moving wall” or to the “filament creation and annihilation” models. Independent of the memristor physics, we discuss two different types of STDP rules that can be implemented with memristors: either the pure timing-based rule that takes into account the arrival time of the spikes from the pre- and...
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