Emerging Memristive Devices for Brain-Inspired Computing and Artificial Perception

被引:5
|
作者
Wang, Jingyu [1 ]
Zhu, Ying [1 ]
Zhu, Li [1 ]
Chen, Chunsheng [1 ]
Wan, Qing [1 ]
机构
[1] Nanjing Univ, Sch Elect Sci & Engn, Nanjing, Peoples R China
来源
关键词
memristor; artificial synapse; artificial neural network; brain-inspired computing; bionic perception; LONG-TERM POTENTIATION; DEEP NEURAL-NETWORKS; SYNAPTIC PLASTICITY; MEMORY; SYNAPSES; TRANSISTORS; REDUCTION;
D O I
10.3389/fnano.2022.940825
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Brain-inspired computing is an emerging field that aims at building a compact and massively parallel architecture, to reduce power consumption in conventional Von Neumann Architecture. Recently, memristive devices have gained great attention due to their immense potential in implementing brain-inspired computing and perception. The conductance of a memristor can be modulated by a voltage pulse, enabling emulations of both essential synaptic and neuronal functions, which are considered as the important building blocks for artificial neural networks. As a result, it is critical to review recent developments of memristive devices in terms of neuromorphic computing and perception applications, waiting for new thoughts and breakthroughs. The device structures, operation mechanisms, and materials are introduced sequentially in this review; additionally, late advances in emergent neuromorphic computing and perception based on memristive devices are summed up. Finally, the challenges that memristive devices toward high-performance brain-inspired computing and perception are also briefly discussed. We believe that the advances and challenges will lead to significant advancements in artificial neural networks and intelligent humanoid robots.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Memristive Devices and Networks for Brain-Inspired Computing
    Zhang, Teng
    Yang, Ke
    Xu, Xiaoyan
    Cai, Yimao
    Yang, Yuchao
    Huang, Ru
    [J]. PHYSICA STATUS SOLIDI-RAPID RESEARCH LETTERS, 2019, 13 (08):
  • [2] Emerging Optoelectronic Devices for Brain-Inspired Computing
    Hu, Lingxiang
    Zhuge, Xia
    Wang, Jingrui
    Wei, Xianhua
    Zhang, Li
    Chai, Yang
    Xue, Xiaoyong
    Ye, Zhizhen
    Zhuge, Fei
    [J]. ADVANCED ELECTRONIC MATERIALS, 2024,
  • [3] Memristive Synapses for Brain-Inspired Computing
    Wang, Jingrui
    Zhuge, Fei
    [J]. ADVANCED MATERIALS TECHNOLOGIES, 2019, 4 (03):
  • [4] Modeling-Based Design of Memristive Devices for Brain-Inspired Computing
    Zhao, Yudi
    Chen, Ruiqi
    Huang, Peng
    Kang, Jinfeng
    [J]. FRONTIERS IN NANOTECHNOLOGY, 2021, 3
  • [5] Memristive crossbar arrays for brain-inspired computing
    Qiangfei Xia
    J. Joshua Yang
    [J]. Nature Materials, 2019, 18 : 309 - 323
  • [6] Memristive crossbar arrays for brain-inspired computing
    Xia, Qiangfei
    Yang, J. Joshua
    [J]. NATURE MATERIALS, 2019, 18 (04) : 309 - 323
  • [7] Biocompatible Memristive Devices for Brain-Inspired Applications
    Han, Aoze
    Zhang, Miaocheng
    Zhang, Liwei
    Chen, Xingyu
    Tong, Yi
    [J]. 2023 7TH IEEE ELECTRON DEVICES TECHNOLOGY & MANUFACTURING CONFERENCE, EDTM, 2023,
  • [8] Artificial neuron operations and spike-timing-dependent plasticity using memristive devices for brain-inspired computing
    Marukame, Takao
    Nishi, Yoshifumi
    Yasuda, Shin-ichi
    Tanamoto, Tetsufumi
    [J]. JAPANESE JOURNAL OF APPLIED PHYSICS, 2018, 57 (04)
  • [9] Artificial neuron operations and spike-timing-dependent plasticity using memristive devices for brain-inspired computing
    Marukame, Takao
    Nishi, Yoshifumi
    Yasuda, Shin-ichi
    Tanamoto, Tetsufumi
    [J]. Japanese Journal of Applied Physics, 2018, 57 (04):
  • [10] Brain-inspired computing with spintronics devices
    Tsunegi, Sumito
    Torrejon, Jacob
    Riou, Mathieu
    Araujo, Flavio Abreu
    Cros, Vincent
    Grollier, Julie
    Yakushiji, Kay
    Fukushima, Akio
    Yuasa, Shinji
    Kubota, Hitoshi
    [J]. 2018 IEEE INTERNATIONAL MEETING FOR FUTURE OF ELECTRON DEVICES, KANSAI (IMFEDK), 2018,