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氧化物神经元器件及其神经网络应用

李宗晓 胡令祥 王敬蕊 诸葛飞

无机材料学报2024,Vol.39Issue(4):345-358,14.
无机材料学报2024,Vol.39Issue(4):345-358,14.DOI:10.15541/jim20230405

氧化物神经元器件及其神经网络应用

Oxide Neuron Devices and Their Applications in Artificial Neural Networks

李宗晓 1胡令祥 1王敬蕊 2诸葛飞3

作者信息

  • 1. 中国科学院 宁波材料技术与工程研究所, 宁波 315201
  • 2. 宁波工程学院 电子与信息工程学院, 宁波 315211
  • 3. 中国科学院 宁波材料技术与工程研究所, 宁波 315201||中国科学院 脑科学与智能技术卓越创新中心, 上海 200031||中国科学院大学 材料与光电研究中心, 北京 100029||浙江大学 温州研究院, 温州 325006
  • 折叠

摘要

Abstract

Nowadays,artificial intelligence(AI)is playing an increasingly important role in human society.Running AI algorithms represented by deep learning places great demands on computational power of hardware.However,with Moore's law approaching physical limitations,the traditional von Neumann computing architecture cannot meet the urgent demand for promoting hardware computational power.The brain-inspired neuromorphic computing(NC)employing an integrated processing-memory architecture is expected to provide an important hardware basis for developing novel AI technologies with low energy consumption and high computational power.Under this conception,artificial neurons and synapses,as the core components of NC systems,have become a research hotspot.This paper aims to provide a comprehensive review on the development of oxide neuron devices.Firstly,several mathematical models of neurons are described.Then,recent progress of Hodgkin-Huxley neurons,leaky integrate-and-fire neurons and oscillatory neurons based on oxide electronic devices is introduced in detail.The effects of device structures and working mechanisms on neuronal performance are systematically analyzed.Next,the hardware implementation of spiking neural networks and oscillatory neural networks based on oxide artificial neurons is demonstrated.Finally,the challenges of oxide neuron devices,arrays and networks,as well as prospect for their applications are pointed out.

关键词

氧化物/神经元器件/类脑计算/神经形态计算/人工神经网络/综述

Key words

oxide/neuron device/brain-inspired computing/neuromorphic computing/artificial neural network/review

分类

数理科学

引用本文复制引用

李宗晓,胡令祥,王敬蕊,诸葛飞..氧化物神经元器件及其神经网络应用[J].无机材料学报,2024,39(4):345-358,14.

基金项目

国家自然科学基金(U20A20209) (U20A20209)

中国科学院战略性先导专项(XDB32050204) (XDB32050204)

中国博士后创新人才支持计划(BX2021326) (BX2021326)

中国博士后科学基金(2021M703310) (2021M703310)

浙江省自然科学基金(LQ22F040003) (LQ22F040003)

宁波市自然科学基金(2021J139,2023J356) (2021J139,2023J356)

环境友好能源材料国家重点实验室开放基金(20kfhg09)National Natural Science Foundation of China(U20A20209) (20kfhg09)

Strategic Priority Research Program of Chinese Academy of Sciences(XDB32050204) (XDB32050204)

China National Postdoctoral Program for Innovative Talents(BX2021326) (BX2021326)

China Postdoctoral Science Foundation(2021M703310) (2021M703310)

Zhejiang Provincial Natural Science Foundation(LQ22F040003) (LQ22F040003)

Ningbo Natural Science Foundation(2021J139,2023J356) (2021J139,2023J356)

State Key Laboratory for Environment-Friendly Energy Materials(20kfhg09) (20kfhg09)

无机材料学报

OA北大核心CSTPCD

1000-324X

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