Forgetting memristor based neuromorphic system for pattern training and recognition

被引:29
|
作者
Zhang, Peijian [1 ]
Li, Chuandong [1 ]
Huang, Tingwen [2 ]
Chen, Ling [1 ]
Chen, Yiran [3 ]
机构
[1] Southwest Univ, Dept Elect & Informat Engn, Chongqing Key Lab Nonlinear Circuits & Intelligen, Chongqing 400715, Peoples R China
[2] Texas A&M Univ Qatar, Dept Math, Doha 23874, Qatar
[3] Univ Pittsburgh, Dept Elect & Comp Engn, Pittsburgh, PA 15261 USA
基金
美国国家科学基金会;
关键词
Memristors; Neuromorphic system; Crossbar; Pattern training and recognition; SYNAPSE; NETWORK; DEVICE;
D O I
10.1016/j.neucom.2016.10.012
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a neuromorphic system for mean variance based pattern training and recognition. The system contains a self-learning circuit, a training circuit and a recognition circuit. Memristor model with forgetting effect which has memory ability and forgetting effect simultaneously is applied to simulate forgetting mechanism of neuromorphic system. Different from previous work, which divided training circuit as off line process, here the weight-changing circuit and the recognition part are combined on line for pattern training and recognition. For illustration, the whole neuromorphic system is applied to recognize handwriting number '0-9' on gray images, and simulations verify its effectiveness.
引用
收藏
页码:47 / 53
页数:7
相关论文
共 50 条
  • [21] Memristor Crossbars for Pattern Recognition
    Mouttet, B.
    NANOTECH CONFERENCE & EXPO 2009, VOL 1, TECHNICAL PROCEEDINGS: NANOTECHNOLOGY 2009: FABRICATION, PARTICLES, CHARACTERIZATION, MEMS, ELECTRONICS AND PHOTONICS, 2009, : 644 - 647
  • [22] Color Recognition Achieved in Multiwavelength Controlled Plasmonic Optoelectronic Memristor for Neuromorphic Visual System
    Cheng, Yankun
    Li, Zhuangzhaung
    Lin, Ya
    Wang, Zhongqiang
    Shan, Xuanyu
    Tao, Ye
    Zhao, Xiaoning
    Xu, Haiyang
    Liu, Yichun
    ADVANCED FUNCTIONAL MATERIALS, 2024,
  • [23] Memristor-Based Neuromorphic Chips
    Duan, Xuegang
    Cao, Zelin
    Gao, Kaikai
    Yan, Wentao
    Sun, Siyu
    Zhou, Guangdong
    Wu, Zhenhua
    Ren, Fenggang
    Sun, Bai
    ADVANCED MATERIALS, 2024, 36 (14)
  • [24] Review on the memristor based neuromorphic chips
    Chen C.
    Luo C.
    Liu S.
    Liu H.
    Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology, 2023, 45 (01): : 1 - 14
  • [25] Memristor-MOS Analog Correlator for Pattern Recognition System
    Han, Ca-Ram
    Lee, Sang-Jin
    Oh, Kwang-Seok
    Cho, Kyoungrok
    JOURNAL OF NANOSCIENCE AND NANOTECHNOLOGY, 2013, 13 (05) : 3365 - 3370
  • [26] 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
  • [27] MNSIM: Simulation Platform for Memristor-Based Neuromorphic Computing System
    Xia, Lixue
    Li, Boxun
    Tang, Tianqi
    Gu, Peng
    Chen, Pai-Yu
    Yu, Shimeng
    Cao, Yu
    Wang, Yu
    Xie, Yuan
    Yang, Huazhong
    IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2018, 37 (05) : 1009 - 1022
  • [28] Reconfigurable Neuromorphic Computing System with Memristor-Based Synapse Design
    Beiye Liu
    Yiran Chen
    Bryant Wysocki
    Tingwen Huang
    Neural Processing Letters, 2015, 41 : 159 - 167
  • [29] Memristor-Based Neuromorphic System with Content Addressable Memory Structure
    Zhu, Yidong
    Wang, Xiao
    Huang, Tingwen
    Zeng, Zhigang
    ADVANCES IN NEURAL NETWORKS - ISNN 2016, 2016, 9719 : 681 - 690
  • [30] Memristor Crossbar-Based Neuromorphic Computing System: A Case Study
    Hu, Miao
    Li, Hai
    Chen, Yiran
    Wu, Qing
    Rose, Garrett S.
    Linderman, Richard W.
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (10) : 1864 - 1878