Emerging memristive neurons for neuromorphic computing and sensing

被引:27
|
作者
Li, Zhiyuan [1 ,2 ]
Tang, Wei [1 ,2 ]
Zhang, Beining [1 ,2 ]
Yang, Rui [1 ,2 ,3 ,4 ]
Miao, Xiangshui [1 ,2 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Integrated Circuits, Sch Opt & Elect Informat, Wuhan, Peoples R China
[2] Hubei Yangtze Memory Labs, Wuhan, Peoples R China
[3] Huazhong Univ Sci & Technol, Sch Integrated Circuits, Wuhan 430074, Peoples R China
[4] Hubei Yangtze Memory Labs, Wuhan 430205, Peoples R China
基金
中国国家自然科学基金;
关键词
Memristive devices; artificial neurons; spiking dynamics; neuromorphic computing; neuromorphic sensing; SPIKE-FREQUENCY ADAPTATION; DEEP NEURAL-NETWORKS; ARTIFICIAL NEURON; ON-CHIP; MODEL; BRAIN; INTELLIGENCE; INFORMATION; ELECTRONICS; THRESHOLD;
D O I
10.1080/14686996.2023.2188878
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Inspired by the principles of the biological nervous system, neuromorphic engineering has brought a promising alternative approach to intelligence computing with high energy efficiency and low consumption. As pivotal components of neuromorphic system, artificial spiking neurons are powerful information processing units and can achieve highly complex nonlinear computations. By leveraging the switching dynamic characteristics of memristive device, memristive neurons show rich spiking behaviors with simple circuit. This report reviews the memristive neurons and their applications in neuromorphic sensing and computing systems. The switching mechanisms that endow memristive devices with rich dynamics and nonlinearity are highlighted, and subsequently various nonlinear spiking neuron behaviors emulated in these memristive devices are reviewed. Then, recent development is introduced on neuromorphic system with memristive neurons for sensing and computing. Finally, we discuss challenges and outlooks of the memristive neurons toward high-performance neuromorphic hardware systems and provide an insightful perspective for the development of interactive neuromorphic electronic systems. [GRAPHICS] .
引用
收藏
页数:23
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