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 |
Appears in Collections: | Elements Staff Publications |
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