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Reservoir computing using back-end-of-line SiC-based memristors

Reservoir computing using back-end-of-line SiC-based memristors
Reservoir computing using back-end-of-line SiC-based memristors

The increasing demand for intellectual computers that can efficiently process substantial amounts of data has resulted in the development of a wide range of nanoelectronics devices. Reservoir computing offers efficient temporal information processing capability with a low training cost. In this work, we demonstrate a back-end-of-line SiC-based memristor that exhibits short-term memory behaviour and is capable of encoding temporal signals. A physical reservoir computing system using our SiC-based memristor as the reservoir has been implemented. This physical reservoir computing system has been experimentally demonstrated to perform the task of pattern recognition. After training, our RC system has achieved 100% accuracy in classifying number patterns from 0 to 9 and demonstrated good robustness to noisy pixels. The results shown here indicate that our SiC-based memristor devices are strong contenders for potential applications in artificial intelligence, particularly in temporal and sequential data processing.

2633-5409
5305-5313
Guo, Dongkai
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Kapur, Omesh
008af9d2-92eb-4749-a3be-210010f63449
Dai, Peng
1150a00a-e54b-438b-bf51-4e8521c07f66
Han, Yisong
9307e57c-85b5-461d-93c5-9c3081224c02
Beanland, Richard
562e4354-94d4-454a-8d45-14e85ececb10
Jiang, Liudi
374f2414-51f0-418f-a316-e7db0d6dc4d1
De Groot, C.H. (Kees)
92cd2e02-fcc4-43da-8816-c86f966be90c
Huang, Ruomeng
55c6fba5-0275-4471-af5c-fb0dd2daaa64
Guo, Dongkai
cc5dd5b1-9e1b-4a86-8f41-7161de1e2e8f
Kapur, Omesh
008af9d2-92eb-4749-a3be-210010f63449
Dai, Peng
1150a00a-e54b-438b-bf51-4e8521c07f66
Han, Yisong
9307e57c-85b5-461d-93c5-9c3081224c02
Beanland, Richard
562e4354-94d4-454a-8d45-14e85ececb10
Jiang, Liudi
374f2414-51f0-418f-a316-e7db0d6dc4d1
De Groot, C.H. (Kees)
92cd2e02-fcc4-43da-8816-c86f966be90c
Huang, Ruomeng
55c6fba5-0275-4471-af5c-fb0dd2daaa64

Guo, Dongkai, Kapur, Omesh, Dai, Peng, Han, Yisong, Beanland, Richard, Jiang, Liudi, De Groot, C.H. (Kees) and Huang, Ruomeng (2023) Reservoir computing using back-end-of-line SiC-based memristors. Materials Advances, 4 (21), 5305-5313. (doi:10.1039/d3ma00141e).

Record type: Article

Abstract

The increasing demand for intellectual computers that can efficiently process substantial amounts of data has resulted in the development of a wide range of nanoelectronics devices. Reservoir computing offers efficient temporal information processing capability with a low training cost. In this work, we demonstrate a back-end-of-line SiC-based memristor that exhibits short-term memory behaviour and is capable of encoding temporal signals. A physical reservoir computing system using our SiC-based memristor as the reservoir has been implemented. This physical reservoir computing system has been experimentally demonstrated to perform the task of pattern recognition. After training, our RC system has achieved 100% accuracy in classifying number patterns from 0 to 9 and demonstrated good robustness to noisy pixels. The results shown here indicate that our SiC-based memristor devices are strong contenders for potential applications in artificial intelligence, particularly in temporal and sequential data processing.

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Accepted/In Press date: 2 October 2023
e-pub ahead of print date: 3 October 2023
Published date: 3 October 2023
Additional Information: Funding Information: R. H. would like to thank the Royal Society for a Research Grant (RGS/R2/222171). O. K. thanks EPSRC and AWE Ltd for the ICASE studentship No. 16000087. All data supporting this study are openly available from the University of Southampton repository at https://doi.org/10.5258/SOTON/D2725. Funding Information: R. H. would like to thank the Royal Society for a Research Grant (RGS/R2/222171). O. K. thanks EPSRC and AWE Ltd for the ICASE studentship No. 16000087. All data supporting this study are openly available from the University of Southampton repository at https://doi.org/10.5258/SOTON/D2725 . Publisher Copyright: © 2023 RSC.

Identifiers

Local EPrints ID: 484293
URI: http://eprints.soton.ac.uk/id/eprint/484293
ISSN: 2633-5409
PURE UUID: f153e817-fabe-4858-b29a-93f6b476a403
ORCID for Peng Dai: ORCID iD orcid.org/0000-0002-5973-9155
ORCID for Liudi Jiang: ORCID iD orcid.org/0000-0002-3400-825X
ORCID for C.H. (Kees) De Groot: ORCID iD orcid.org/0000-0002-3850-7101

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Date deposited: 13 Nov 2023 18:58
Last modified: 06 Jun 2024 01:43

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Contributors

Author: Dongkai Guo
Author: Omesh Kapur
Author: Peng Dai ORCID iD
Author: Yisong Han
Author: Richard Beanland
Author: Liudi Jiang ORCID iD
Author: Ruomeng Huang

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