A delay system reservoir based on a nano-ionic Solid Electrolyte FET*

De Souza, M.M. orcid.org/0000-0002-7804-7154, Song, X., Gaurav, A. et al. (6 more authors) (2023) A delay system reservoir based on a nano-ionic Solid Electrolyte FET*. In: 2023 IEEE Nanotechnology Materials and Devices Conference (NMDC). 2023 IEEE Nanotechnology Materials and Devices Conference (NMDC), 22-25 Oct 2023, Paestum, Italy. Institute of Electrical and Electronics Engineers (IEEE) , pp. 139-140. ISBN 9798350335460

Abstract

Reservoir computing using delay systems took off when it was demonstrated that a single volatile memristor can be effectively utilized to reduce the burden of training recurrent neural networks, without the need for any interconnected reservoir nodes. Here we demonstrate that the maximum impact on the learning efficiency of a ZnO/Ta2O5 SEFET based reservoir is derived from (i) training the output after every pulse, (ii) device variability, and (iii) scanning the input image data horizontally and vertically.

Metadata

Item Type:	Proceedings Paper
Authors/Creators:	De Souza, M.M. https://orcid.org/0000-0002-7804-7154 Song, X. Gaurav, A. Manhas, S.K. Pillai, P.B. Sikdar, S. Kumar, A. Gilra, A. Vasilaki, E. https://orcid.org/0000-0003-3705-7070
Copyright, Publisher and Additional Information:	© 2024 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in 2023 IEEE Nanotechnology Materials and Devices Conference (NMDC) is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/
Keywords:	Training; Resistance; Solid modeling; Delay systems; Memristors; Voltage; Logic gates; Recurrent Neural Network; Voltage-gated; Read Voltage
Dates:	Published: 12 December 2023 Published (online): 12 December 2023
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield)
Depositing User:	Symplectic Sheffield
Date Deposited:	26 Feb 2024 12:26
Last Modified:	26 Feb 2024 12:26
Status:	Published
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Refereed:	Yes
Identification Number:	10.1109/nmdc57951.2023.10344264
Related URLs:	Conference
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:209584

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A delay system reservoir based on a nano-ionic Solid Electrolyte FET*

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