Neuromorphic Properties of Memristor towards Artificial Intelligence

Zhao, C;Shen, ZJ;Zhou, GY;Zhao, CZ;Yang, L;Man, KL;Lim, EG

[Zhao, Chun; Shen, Zong Jie; Zhou, Guang You; Zhao, Ce Zhou; Yang, Li; Man, Ka Lok; Lim, Eng Gee] Xian Jiatong Liverpool Univ, AI URC, Suzhou, Peoples R China.

2018 INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC)

Pages:172-173

DOI:10.1109/ISOCC.2018.8649926

Publication Year:2018

Document Type:Conference Paper

Identifier:http://hdl.handle.net/20.500.12791/001959

Abstract

Recent implementations of memristors have opened up the possibility of making brain-like artificial intelligence neuromorphic computing systems, including highly scalable and low-power neural networks. In fact, it has been demonstrated that a memristors can be implemented as an artificial synapse or as a protruding core of an artificial neuron. This paper reviews the neuromorphic properties of memristors, as well as the similarities of neural computation, synapses, and neurons.

Keywords

Artificial Neural Network Memristor Neuromorphic

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