神经形态工程学
记忆电阻器
冯·诺依曼建筑
领域(数学)
计算机科学
计算机体系结构
人工智能
工程类
电气工程
人工神经网络
数学
纯数学
操作系统
作者
Rui Guo,Weinan Lin,Xiaobing Yan,T. Venkatesan,Jingsheng Chen
摘要
Brain-inspired neuromorphic computing has been intensively studied due to its potential to address the inherent energy and throughput limitations of conventional Von-Neumann based computing architecture. Memristors are ideal building blocks for artificial synapses, which are the fundamental components of neuromorphic computing. In recent years, the emerging ferroic (ferroelectric and ferromagnetic) tunnel junctions have been shown to be able to function as memristors, which are potential candidates to emulate artificial synapses for neuromorphic computing. Here, we provide a review on the ferroic tunnel junctions and their applications as artificial synapses in neuromorphic networks. We focus on the development history of ferroic tunnel junctions, their physical conduction mechanisms, and the intrinsic dynamics of memristors. Their current applications in neuromorphic networks will also be discussed. Finally, a conclusion and future outlooks on the development of ferroic tunnel junctions will be given. Our goal is to give a broad review of ferroic tunnel junction based artificial synapses that can be applied to neuromorphic computing and to help further ongoing research in this field.
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