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*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number012002
JournalInternational Journal of Extreme Manufacturing
Volume7
Issue number1
DOIs
Publication statusPublished - 1 Feb 2025

Keywords

  • compute-in-memory
  • in-sensor computing
  • memristive device fabrication
  • reservoir computing

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