Analog–digital hybrid computing with SnS2 memtransistor for low-powered sensor fusion

Shania Rehman; Muhammad Farooq Khan; Hee-Dong Kim; Sungho Kim

doi:10.1038/s41467-022-30564-5

Nature Communications (May 2022)

Analog–digital hybrid computing with SnS2 memtransistor for low-powered sensor fusion

Shania Rehman,
Muhammad Farooq Khan,
Hee-Dong Kim,
Sungho Kim

Affiliations

Shania Rehman: Department of Electrical Engineering and Convergence Engineering for Intelligent Drone, Sejong University
Muhammad Farooq Khan: Department of Electrical Engineering and Convergence Engineering for Intelligent Drone, Sejong University
Hee-Dong Kim: Department of Electrical Engineering and Convergence Engineering for Intelligent Drone, Sejong University
Sungho Kim: Department of Electrical Engineering and Convergence Engineering for Intelligent Drone, Sejong University

DOI: https://doi.org/10.1038/s41467-022-30564-5
Journal volume & issue: Vol. 13, no. 1
pp. 1 – 8

Abstract

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Analog–digital hybrid computing based on SnS2 memtransistors is demonstrated for lowpower sensor fusion in drones, where a drone with hybrid computing performs sensor fusion with higher energy efficiency than that with only a digital processor.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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