神经形态器件的特性与发展

曹震; 张浴轩; 李灵蕾; 郭璋; 孙琦; 曹荣荣; 侯彪; 焦李成

doi:10.12263/DZXB.20230458

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神经形态器件的特性与发展

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- 神经形态器件的特性与发展
- A Comprehension Survey on the Characterization and Development of Neuromorphic Devices
- 电子学报 2023年51卷第12期页码：3619-3642
- 作者机构：
  
  1.西安电子科技大学人工智能学院,陕西西安 710126
  2.西安电子科技大学杭州研究院,浙江杭州 311231
  3.国防科技大学电子科学学院,湖南长沙 410073
- 作者简介：
  
  [ "曹震男，1989年3月出生于山东省微山县.现为西安电子科技大学人工智能学院华山学者准聘副教授、硕士生导师.主要研究方向为微电子器件设计与人工智能优化方法前沿交叉、脉冲神经网络FPGA、智能芯片设计与智能系统等. E-mail: caozhen@xidian.edu.cn" ]
  [ "张浴轩男，1999年4月出生于辽宁省沈阳市.2022年于西安邮电大学计算机学院获学士学位，现为西安电子科技大学人工智能学院硕士研究生.主要研究方向为神经网络FPGA硬件边缘部署. E-mail: 22171214686@stu.xidian.edu.cn" ]
  [ "李灵蕾女，2002年2月出生于山西省太原市.现为西安电子科技大学人工智能学院智能科学与技术专业硕士研究生. E-mail: linglei_li@163.com" ]
  [ "郭璋男，1991年8月21日生于陕西省渭南市.现为西安电子科技大学前沿交叉研究院华山学者准聘副教授、硕士生导师.主要研究方向为忆阻器与神经形态器件、类脑计算与人工智能、状态监测与故障诊断等. E-mail: guozhang@xidian.edu.cn" ]
  [ "孙琦男，2002年3月出生于湖北省孝感市.2023年于西安电子科技大学大学人工智能学院获学士学位，现为西安电子科技大学人工智能学院硕士研究生.主要研究方向为人工智能半导体交叉. E-mail: 23171214665@stu.xidian.edu.cn" ]
  [ "曹荣荣女，1990年6月出生于山东省临沂市.现为国防科技大学电子科学学院副教授、硕士生导师，青年托举人才、湖南省湖湘英才.主要研究方向为新原理智能信息器件开发及其类脑计算. E-mail: caorongrong@nudt.edu.cn" ]
  [ "侯彪男，1974年11月出生于陕西省宝鸡市.现为西安电子科技大学人工智能学院华山学者特聘教授、博士生导师.主要研究方向为遥感图像解译与目标识别、无人系统协同感知、人工智能芯片及系统等. E-mail: avcodec@163.com" ]
  [ "焦李成男，1959年10月出生于陕西省白水县.现为西安电子科技大学人工智能研究院华山学者杰出教授，欧洲科学院外籍院士、俄罗斯自然科学院外籍院士、IEEE Fellow.主要研究方向为智能感知与图像理解、深度学习与类脑计算、进化优化与遥感解译. E-mail: lchjiao@mail.xidian.edu.cn" ]
- 基金信息：
  
  国家自然科学基金(62104176;62171347;62004220;62301395);中国博士后科学基金(2019M663637;2020M673696);西安电子科技大学杭州研究院概念验证基金(GNYZ2023XJ0409-1);陕西省自然科学基础研究计划(2022JQ-661);中央高校基本科研业务费专项资金项目(XJSJ23083;XJS222215)
- DOI：10.12263/DZXB.20230458
  中图分类号： TP183;
- 收稿：2023-05-25，
  
  修回：2023-10-08，
  
  纸质出版：2023-12-25
- 稿件说明：
移动端阅览
曹震,张浴轩,李灵蕾等.神经形态器件的特性与发展[J].电子学报,2023,51(12):3619-3642.

CAO Zhen,ZHANG Yu-xuan,LI Ling-lei,et al.A Comprehension Survey on the Characterization and Development of Neuromorphic Devices[J].ACTA ELECTRONICA SINICA,2023,51(12):3619-3642.
曹震,张浴轩,李灵蕾等.神经形态器件的特性与发展[J].电子学报,2023,51(12):3619-3642. DOI： 10.12263/DZXB.20230458.

CAO Zhen,ZHANG Yu-xuan,LI Ling-lei,et al.A Comprehension Survey on the Characterization and Development of Neuromorphic Devices[J].ACTA ELECTRONICA SINICA,2023,51(12):3619-3642. DOI： 10.12263/DZXB.20230458.

摘要

随着大数据时代的到来和人类对人脑系统研究的日渐深入，类脑计算领域的研究取得突破性进展，有希望在根源上打破传统计算机的性能瓶颈.神经突触是对人体脑部进行记忆能力训练和处理数据的重要基础单元，因此开发新材料、新结构，研究基于新型人造材料与光电子器件的神经突触可塑性，对神经形态器件研究和类脑硬件设计的实现都有着重要意义.本文首先指出目前“冯·诺依曼架构”的主要性能瓶颈，引出类脑计算的概念，提出神经形态器件的主要性能优势，并梳理神经形态器件发展历史；然后在忆阻器领域，阐述与分析忆阻类型、忆阻结构与忆阻机理，比较出几种忆阻器的特性，举例说明忆阻器在不同领域的应用；接着以神经形态器件为基础，选取磁性隧道结、新型浮栅管和铁电晶体管，介绍其结构、工作原理与应用；最后总结目前神经形态器件发展的成果和方向，并对行业发展前景进行预测.

Abstract

With the advent of the big data era and the increasingly in-depth study of the human brain system

the field of neuromorphic computing has made breakthrough progress

offering hope to break through the performance issue of traditional computers at the root level. Neural synapses are important basic units for memory training and data processing in the human brain

therefore

it is of great significance for research on neural morphological devices and the implementation of neuromorphic hardware design to develop new materials and structures to study the plasticity of neural synapses based on novel artificial materials and optoelectronic devices. This paper firstly points out the main performance issue of Von Neumann architecture

draws forth the concept of brain-like computing

puts forward the main performance advantages of neuromorphic devices

and sorts out the development history of neuromorphic devices. Then in the field of memristors

the types of memristors

memristor structures and memristor mechanisms are described and analyzed

the advantages and disadvantages of several types of memristors are compared

and the examples of applications of memristors in different fields are presented. Next

based on neural morphological devices

the structures

working principles and applications of magnetic tunnel junctions

new floating gate transistors

and ferroelectric transistors are selected to introduce. Finally

this paper summarizes the achievements and directions of the current development of neural morphological devices and predicts the development prospects of the industry.

关键词

Keywords

references

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