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Nano device fabrication for in-memory and in-sensor reservoir computing

  • Yinan Lin
  • , Xi Chen
  • , Qianyu Zhang
  • , Junqi You
  • , Renjing Xu
  • , Zhongrui Wang*
  • , Linfeng Sun*
  • *此作品的通讯作者
  • Beijing Institute of Technology
  • The University of Hong Kong
  • Hong Kong Science Park
  • The Hong Kong University of Science and Technology (Guangzhou)
  • Southern University of Science and Technology

科研成果: 期刊稿件文献综述同行评审

摘要

Highlights Reservoir computing (RC), with its smaller network size and straightforward training process, has become a popular machine learning algorithm in the current landscape. Nano-memristors, characterized by their high integration density and the ability to achieve storage and computation in a unified manner, are regarded as promising devices to accelerate machine learning. The aim of current study is to present the current applications of in-memory and in-sensor RC based on nano-memristors and to outline the potential developments for the next steps.

源语言英语
期刊论文编号012002
期刊International Journal of Extreme Manufacturing
7
1
DOI
出版状态已出版 - 1 2月 2025

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