Please use this identifier to cite or link to this item: https://doi.org/10.3389/fnano.2021.645995
Title: Advances in Memristor-Based Neural Networks
Authors: Xu, W.
Wang, J.
Yan Xiaobing 
Keywords: artificial intelligence
artificial neural network
integrated circuit
memristor
spiking neural network
Issue Date: 24-Mar-2021
Publisher: Frontiers Media S.A.
Citation: Xu, W., Wang, J., Yan Xiaobing (2021-03-24). Advances in Memristor-Based Neural Networks. Frontiers in Nanotechnology 3 : 645995. ScholarBank@NUS Repository. https://doi.org/10.3389/fnano.2021.645995
Rights: Attribution 4.0 International
Abstract: The rapid development of artificial intelligence (AI), big data analytics, cloud computing, and Internet of Things applications expect the emerging memristor devices and their hardware systems to solve massive data calculation with low power consumption and small chip area. This paper provides an overview of memristor device characteristics, models, synapse circuits, and neural network applications, especially for artificial neural networks and spiking neural networks. It also provides research summaries, comparisons, limitations, challenges, and future work opportunities. Copyright © 2021 Xu, Wang and Yan.
Source Title: Frontiers in Nanotechnology
URI: https://scholarbank.nus.edu.sg/handle/10635/232817
ISSN: 2673-3013
DOI: 10.3389/fnano.2021.645995
Rights: Attribution 4.0 International
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