Emerging Memristive Devices for Brain-Inspired Computing and Artificial Perception

被引:5
|
作者
Wang, Jingyu [1 ]
Zhu, Ying [1 ]
Zhu, Li [1 ]
Chen, Chunsheng [1 ]
Wan, Qing [1 ]
机构
[1] Nanjing Univ, Sch Elect Sci & Engn, Nanjing, Peoples R China
来源
关键词
memristor; artificial synapse; artificial neural network; brain-inspired computing; bionic perception; LONG-TERM POTENTIATION; DEEP NEURAL-NETWORKS; SYNAPTIC PLASTICITY; MEMORY; SYNAPSES; TRANSISTORS; REDUCTION;
D O I
10.3389/fnano.2022.940825
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Brain-inspired computing is an emerging field that aims at building a compact and massively parallel architecture, to reduce power consumption in conventional Von Neumann Architecture. Recently, memristive devices have gained great attention due to their immense potential in implementing brain-inspired computing and perception. The conductance of a memristor can be modulated by a voltage pulse, enabling emulations of both essential synaptic and neuronal functions, which are considered as the important building blocks for artificial neural networks. As a result, it is critical to review recent developments of memristive devices in terms of neuromorphic computing and perception applications, waiting for new thoughts and breakthroughs. The device structures, operation mechanisms, and materials are introduced sequentially in this review; additionally, late advances in emergent neuromorphic computing and perception based on memristive devices are summed up. Finally, the challenges that memristive devices toward high-performance brain-inspired computing and perception are also briefly discussed. We believe that the advances and challenges will lead to significant advancements in artificial neural networks and intelligent humanoid robots.
引用
收藏
页数:17
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