Nanoscale Memristor Device as Synapse in Neuromorphic Systems

被引:3345
|
作者
Jo, Sung Hyun [1 ]
Chang, Ting [1 ]
Ebong, Idongesit [1 ]
Bhadviya, Bhavitavya B. [1 ]
Mazumder, Pinaki [1 ]
Lu, Wei [1 ]
机构
[1] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会;
关键词
Nanoelectronics; neuromorphic system; memristor; synaptic adaptation; spike-timing dependent plasticity; RESISTANCE; MODEL;
D O I
10.1021/nl904092h
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
A memristor is a two-terminal electronic device whose conductance can be precisely modulated by charge or flux through it. Here we experimentally demonstrate a nanoscale silicon-based memristor device and show that a hybrid system composed of complementary metal oxide semiconductor neurons and memristor synapses can support important synaptic functions such as spike timing dependent plasticity. Using memristors as synapses in neuromorphic circuits can potentially offer both high connectivity and high density required for efficient computing.
引用
收藏
页码:1297 / 1301
页数:5
相关论文
共 50 条
  • [1] Analysis of the Memristor-Based Crossbar Synapse for Neuromorphic Systems
    Kim, Bokyung
    Jo, Sumin
    Sun, Wookyung
    Shin, Hyungsoon
    JOURNAL OF NANOSCIENCE AND NANOTECHNOLOGY, 2019, 19 (10) : 6703 - 6709
  • [2] Fusion synapse by memristor and capacitor for spiking neuromorphic systems
    Kuwahara, Takumi
    Oshio, Reon
    Kimura, Mutsumi
    Zhang, Renyuan
    Nakashima, Yasuhiko
    NEUROCOMPUTING, 2024, 593
  • [3] A Hybrid CMOS-Memristor Neuromorphic Synapse
    Azghadi, Mostafa Rahimi
    Linares-Barranco, Bernabe
    Abbott, Derek
    Leong, Philip H. W.
    IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2017, 11 (02) : 434 - 445
  • [4] An electronic synapse device based on aluminum nitride memristor for neuromorphic computing application
    Guo, Yuanyang
    Hu, Wei
    Zhang, Changgeng
    Peng, Yao
    Guo, Yongcai
    JOURNAL OF PHYSICS D-APPLIED PHYSICS, 2020, 53 (19)
  • [5] Optimizations for a Current-Controlled Memristor- Based Neuromorphic Synapse Design
    Das, Hritom
    Febbo, Rocco D.
    Rizzo, Charles P.
    Chakraborty, Nishith N.
    Plank, James S.
    Rose, Garrett S.
    IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS, 2023, 13 (04) : 889 - 900
  • [6] Metallopolymeric Memristor Based Artificial Optoelectronic Synapse for Neuromorphic Computing
    Cheng, Xiaozhe
    Qin, Zhitao
    Guo, Hongen
    Dou, Zhitao
    Lian, Hong
    Fan, Jianfeng
    Qu, Yongquan
    Dong, Qingchen
    ACS APPLIED ELECTRONIC MATERIALS, 2024, 6 (06) : 4345 - 4355
  • [7] Integration of nanoscale memristor synapses in neuromorphic computing architectures
    Indiveri, Giacomo
    Linares-Barranco, Bernabe
    Legenstein, Robert
    Deligeorgis, George
    Prodromakis, Themistoklis
    NANOTECHNOLOGY, 2013, 24 (38)
  • [8] A Bi-Memristor Synapse with Spike-Timing-Dependent Plasticity for On-Chip Learning in Memristive Neuromorphic Systems
    Sayyaparaju, Sagarvarma
    Amer, Sherif
    Rose, Garrett S.
    2018 19TH INTERNATIONAL SYMPOSIUM ON QUALITY ELECTRONIC DESIGN (ISQED), 2018, : 69 - 74
  • [9] Reconfigurable Neuromorphic Computing System with Memristor-Based Synapse Design
    Liu, Beiye
    Chen, Yiran
    Wysocki, Bryant
    Huang, Tingwen
    NEURAL PROCESSING LETTERS, 2015, 41 (02) : 159 - 167
  • [10] Reconfigurable Neuromorphic Computing System with Memristor-Based Synapse Design
    Beiye Liu
    Yiran Chen
    Bryant Wysocki
    Tingwen Huang
    Neural Processing Letters, 2015, 41 : 159 - 167