Artificial Astrocyte Memristor with Recoverable Linearity for Neuromorphic Computing

被引:10
|
作者
Cheng, Caidie [1 ,2 ]
Wang, Yanghao [2 ]
Xu, Liying [2 ]
Liu, Keqin [2 ]
Dang, Bingjie [2 ]
Lu, Yingming [2 ]
Yan, Xiaoqin [1 ]
Huang, Ru [2 ,3 ,4 ]
Yang, Yuchao [2 ,3 ,4 ]
机构
[1] Univ Sci & Technol Beijing, Sch Mat Sci & Engn, State Key Lab Adv Met & Mat, Beijing 100083, Peoples R China
[2] Peking Univ, Sch Integrated Circuits, Key Lab Microelect Devices & Circuits MOE, Beijing 100871, Peoples R China
[3] Peking Univ, Inst Artificial Intelligence, Ctr Brain Inspired Chips, Beijing 100871, Peoples R China
[4] Chinese Inst Brain Res CIBR, Ctr Brain Inspired Intelligence, Beijing 102206, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
artificial astrocyte; image recognition; memristor; neuromorphic computing; nonlinearity; TAOX;
D O I
10.1002/aelm.202100669
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Neuromorphic systems provide a potential solution for overcoming von Neumann bottleneck and realizing computing with low energy consumption and latency. However, the neuromorphic devices utilized to construct the neuromorphic systems always focus on artificial synapses and neurons, and neglected the important role of astrocyte cells. Here, an astrocyte memristor is demonstrated with encapsulated yttria-stabilized zirconia (YSZ) to emulate the function of astrocyte cells in biology. Due to the high oxygen vacancy concentration and resultant high ionic conductivity of YSZ, significantly lower forming and set voltages are achieved in the artificial astrocyte, along with high endurance (>10(11)). More importantly, the nonlinearity in current-voltage characteristics that usually emerge as the testing cycle increases can be depressed in the astrocyte memristor, and the nonlinearity can also be reversed by applying a refresh operation, which implements the role of biological astrocyte in maintaining the normal activity of neurons. The recovery of linearity can dramatically improve the accuracy of Modified National Institute of Standards and Technology dataset classification from 62.98% to 94.75% when the inputs are encoded in voltage amplitudes. The astrocyte memristor in this work with improved performance and linearity recovery characteristics can well emulate the function of astrocyte cells in biology and have great potential for neuromorphic computing.
引用
收藏
页数:7
相关论文
共 50 条
  • [21] Challenges of memristor based neuromorphic computing system
    Bonan YAN
    Yiran CHEN
    Hai LI
    ScienceChina(InformationSciences), 2018, 61 (06) : 162 - 164
  • [22] Challenges of memristor based neuromorphic computing system
    Yan, Bonan
    Chen, Yiran
    Li, Hai
    SCIENCE CHINA-INFORMATION SCIENCES, 2018, 61 (06)
  • [23] Ferroelectric memristor and its neuromorphic computing applications
    Du, Junmei
    Sun, Bai
    Yang, Chuan
    Cao, Zelin
    Zhou, Guangdong
    Wang, Hongyan
    Chen, Yuanzheng
    MATERIALS TODAY PHYSICS, 2025, 50
  • [24] Volatile tin oxide memristor for neuromorphic computing
    Ju, Dongyeol
    Kim, Sungjun
    ISCIENCE, 2024, 27 (08)
  • [25] PAWN: Programmed Analog Weights for Non-Linearity Optimization in Memristor-Based Neuromorphic Computing System
    Khan, Saleh Ahmad
    Oli-Uz-Zaman, Md.
    Wang, Jinhui
    IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS, 2023, 13 (01) : 436 - 444
  • [26] Neuromorphic Properties of Memristor towards Artificial Intelligence
    Zhao, Chun
    Shen, Zong Jie
    Zhou, Guang You
    Zhao, Ce Zhou
    Yang, Li
    Man, Ka Lok
    Lim, Eng Gee
    2018 INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC), 2018, : 172 - 173
  • [27] Dual-terminal artificial synapse in two-dimensional CrSBr memristor for neuromorphic computing
    Li, Zhi
    Liu, Ruiqi
    Chu, Yafei
    Feng, Sihua
    Lan, Weican
    Duan, Hengli
    Liu, Chaocheng
    Yan, Wensheng
    JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS, 2024, 35 (16)
  • [28] CMOS-Compatible Memristor for Optoelectronic Neuromorphic Computing
    Facai Wu
    Chien-Hung Chou
    Tseung-Yuen Tseng
    Nanoscale Research Letters, 17
  • [29] Cascaded Neural Network for Memristor based Neuromorphic Computing
    Sun, Sheng-Yang
    Xu, Hui
    Li, Jiwei
    Liu, Haijun
    Li, Qingjiang
    2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2019,
  • [30] Organic Memristor with Synaptic Plasticity for Neuromorphic Computing Applications
    Zeng, Jianmin
    Chen, Xinhui
    Liu, Shuzhi
    Chen, Qilai
    Liu, Gang
    NANOMATERIALS, 2023, 13 (05)