Recent Progress in Optoelectronic Synapses for Artificial Visual-Perception System

被引:73
作者
Han, Xun [1 ]
Xu, Zhangsheng [2 ]
Wu, Wenqiang [2 ]
Liu, Xianhu [3 ,4 ]
Yan, Peiguang [1 ]
Pan, Caofeng [1 ,2 ]
机构
[1] Shenzhen Univ, Coll Phys & Optoelect Engn, Shenzhen 518060, Peoples R China
[2] Chinese Acad Sci, Beijing Inst Nanoenergy & Nanosyst, Beijing Key Lab Micronano Energy & Sensor, CAS Ctr Excellence Nanosci, Beijing 100083, Peoples R China
[3] Zhengzhou Univ, Minist Educ, Key Lab Mat Proc & Mold, Zhengzhou 450002, Henan, Peoples R China
[4] Zhengzhou Univ, Natl Engn Res Ctr Adv Polymer Proc Technol, Zhengzhou 450002, Henan, Peoples R China
来源
SMALL STRUCTURES | 2020年 / 1卷 / 03期
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
artificial visual-perception systems; neuromorphic computing; optoelectronic synapses; synaptic behaviors; RESISTIVE SWITCHING MEMORY; TERM SYNAPTIC PLASTICITY; NEURAL-NETWORKS; SENSOR MATRIX; PRESSURE; DEVICE; SEMICONDUCTOR; FUNDAMENTALS; TRANSISTORS; RECOGNITION;
D O I
10.1002/sstr.202000029
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The human visual system undertakes most of the information perceiving tasks, and nearly 80% of the perceived information is obtained via the visual system. The basic functions of the human visual system can be emulated by neuromorphic visual-perception systems in the light region from UV to near-IR. An optoelectronic synapse served as the basic unit of the neuromorphic visual-perception system is required to combine photosensing function and synaptic element. In addition, optoelectronic synapses demonstrate the prospective advantage of large bandwidth, ultrafast signal transmission, and low electrical energy loss, which is expected in the photonic signal-triggered computing. This work reviews recent progress in the optoelectrical synapses. Device architectures and working mechanisms are discussed. The applications in the artificial visual-perception system for image memorization and pattern recognition are reviewed. The main challenges and opportunities of optoelectrical synapses are also presented.
引用
收藏
页数:18
相关论文
共 135 条
  • [1] Synaptic computation
    Abbott, LF
    Regehr, WG
    [J]. NATURE, 2004, 431 (7010) : 796 - 803
  • [2] Metal Oxide Thin Film Phototransistor for Remote Touch Interactive Displays
    Ahn, Seung-Eon
    Song, Ihun
    Jeon, Sanghun
    Jeon, Youg Woo
    Kim, Young
    Kim, Changjung
    Ryu, Byungki
    Lee, Je-Hun
    Nathan, Arokia
    Lee, Sungsik
    Kim, Gyu Tae
    Chung, U-In
    [J]. ADVANCED MATERIALS, 2012, 24 (19) : 2631 - 2636
  • [3] Mimicking Neurotransmitter Release in Chemical Synapses via Hysteresis Engineering in MoS2 Transistors
    Arnold, Andrew J.
    Razavieh, Ali
    Nasr, Joseph R.
    Schulman, Daniel S.
    Eichfeld, Chad M.
    Das, Saptarshi
    [J]. ACS NANO, 2017, 11 (03) : 3110 - 3118
  • [4] Light-Emission Enhancement in a Flexible and Size-Controllable ZnO Nanowire/Organic Light-Emitting Diode Array by the Piezotronic Effect
    Bao, Rongrong
    Wang, Chunfeng
    Peng, Zhengchun
    Ma, Chuang
    Dong, Lin
    Pan, Caofeng
    [J]. ACS PHOTONICS, 2017, 4 (06): : 1344 - 1349
  • [5] CdS nanorods/organic hybrid LED array and the piezo-phototronic effect of the device for pressure mapping
    Bao, Rongrong
    Wang, Chunfeng
    Dong, Lin
    Shen, Changyu
    Zhao, Kun
    Pan, Caofeng
    [J]. NANOSCALE, 2016, 8 (15) : 8078 - 8082
  • [6] Flexible and Controllable Piezo-Phototronic Pressure Mapping Sensor Matrix by ZnO NW/p-Polymer LED Array
    Bao, Rongrong
    Wang, Chunfeng
    Dong, Lin
    Yu, Ruomeng
    Zhao, Kun
    Wang, Zhong Lin
    Pan, Caofeng
    [J]. ADVANCED FUNCTIONAL MATERIALS, 2015, 25 (19) : 2884 - 2891
  • [7] Artificial neural networks: fundamentals, computing, design, and application
    Basheer, IA
    Hajmeer, M
    [J]. JOURNAL OF MICROBIOLOGICAL METHODS, 2000, 43 (01) : 3 - 31
  • [8] Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits
    Bayat, F. Merrikh
    Prezioso, M.
    Chakrabarti, B.
    Nili, H.
    Kataeva, I.
    Strukov, D.
    [J]. NATURE COMMUNICATIONS, 2018, 9
  • [9] A quantitative model for charge carrier transport, trapping and recombination in nanocrystal-based solar cells
    Bozyigit, Deniz
    Lin, Weyde M. M.
    Yazdani, Nuri
    Yarema, Olesya
    Wood, Vanessa
    [J]. NATURE COMMUNICATIONS, 2015, 6
  • [10] Spike timing-dependent plasticity: A Hebbian learning rule
    Caporale, Natalia
    Dan, Yang
    [J]. ANNUAL REVIEW OF NEUROSCIENCE, 2008, 31 : 25 - 46