基于纳米线的神经形态计算突触装置

Xue Chen, Bingkun Chen, Pengfei Zhao, Vellaisamy A. L. Roy, Su‐Ting Han, Ye Zhou
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引用次数: 6

摘要

传统的冯诺依曼结构计算机已不能满足高速大数据处理的需求;因此,近年来神经形态计算受到了广泛的关注。基于大脑的神经形态计算具有功耗低、速度快、精度高等优点。在人脑中,数据的传输和处理是通过突触来实现的。人工突触装置可以模拟生物突触的功能。纳米线(NW)是纳米电子学和光电子学的重要组成部分,在神经形态计算中,基于纳米线的突触器件的应用得到了广泛的推广。在这里,我们将介绍基于nw的突触忆阻器和突触晶体管的最新进展。本文将讨论基于nw的突触装置在神经形态计算中的应用。提出了基于nw的突触器件所面临的挑战。我们希望这一观点将有助于基于nw的突触装置在神经形态系统中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nanowire-based synaptic devices for neuromorphic computing
The traditional von Neumann structure computers cannot meet the demands of high-speed big data processing; therefore, neuromorphic computing has received a lot of interest in recent years. Brain-inspired neuromorphic computing has the advantages of low power consumption, high speed and high accuracy. In human brains, the data transmission and processing are realized through synapses. Artificial synaptic devices can be adopted to mimic the biological synaptic functionalities. Nanowire (NW) is an important building block for nanoelectronics and optoelectronics, and many efforts have been made to promote the application of NW-based synaptic devices for neuromorphic computing. Here, we will introduce the current progress of NW-based synaptic memristors and synaptic transistors. The applications of NW-based synaptic devices for neuromorphic computing will be discussed. The challenges faced by NW-based synaptic devices will be proposed. We hope this perspective will be beneficial for the application of NW-based synaptic devices in neuromorphic systems.
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