神经形态工程学
材料科学
光电子学
记忆电阻器
冯·诺依曼建筑
瓶颈
晶体管
电子工程
计算机体系结构
电气工程
电压
计算机科学
工程类
嵌入式系统
人工智能
人工神经网络
操作系统
作者
Xiaoyu Wang,Yixin Zong,Duan-Yang Liu,Juehan Yang,Zhongming Wei
标识
DOI:10.1002/adfm.202213894
摘要
Abstract Neuromorphic systems can parallelize the perception and computation of information, making it possible to break through the von Neumann bottleneck. Neuromorphic engineering has been developed over a long period of time based on Hebbian learning rules. The optoelectronic neuromorphic analog device combines the advantages of electricity and optics, and can simulate the biological visual system, which has a very strong development potential. Low‐dimensional materials play a very important role in the field of optoelectronic neuromorphic devices due to their flexible bandgap tuning mechanism and strong light‐matter coupling efficiency. This review introduces the basic synaptic plasticity of neuromorphic devices. According to the different number of terminals, two‐terminal neuromorphic memristors, three‐terminal neuromorphic transistors and artificial visual system are introduced from the aspects of the action mechanism and device structure. Finally, the development prospect of optoelectronic neuromorphic analog devices based on low‐dimensional materials is prospected.
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