Opened Access A Hybrid CMOS-Memristor Neuromorphic Synapse

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Autor: Azghadi, Mostafa, R.
Linares Barranco, Bernabé
Abbott, Derek
Leong, Philip H.W.
Departamento: Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores
Fecha: 2017
Publicado en: IEEE Transactions on Biomedical Circuits and Systems, 11, 434-445.
Tipo de documento: Artículo
Resumen: Although data processing technology continues to advance at an astonishing rate, computers with brain-like processing capabilities still elude us. It is envisioned that such computers may be achieved by the fusion of neuroscience and nano-electronics to realize a brain-inspired platform. This paper proposes a high-performance nano-scale Complementary Metal Oxide Semiconductor (CMOS)-memristive circuit, which mimics a number of essential learning properties of biological synapses. The proposed synaptic circuit that is composed of memristors and CMOS transistors, alters its memristance in response to timing differences among its pre-and post-synaptic action potentials, giving rise to a family of Spike Timing Dependent Plasticity (STDP). The presented design advances preceding memristive synapse designs with regards to the ability to replicate essential behaviours characterised in a number of electrophysiological experiments performed in the animal brain, which involve higher order spike...
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Cita: Azghadi, M., Linares Barranco, B., Abbott, D. y Leong, P.H.W. (2017). A Hybrid CMOS-Memristor Neuromorphic Synapse. IEEE Transactions on Biomedical Circuits and Systems, 11, 434-445.
Tamaño: 1.873Mb
Formato: PDF

URI: https://hdl.handle.net/11441/72478

DOI: 10.1109/TBCAS.2016.2618351

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