A solid electrolyte ZnO thin film transistor for classification of spoken digits using Reservoir Computing

Gaurav, A., Song, X., Manhas, S.K. et al. (2 more authors) (2023) A solid electrolyte ZnO thin film transistor for classification of spoken digits using Reservoir Computing. In: 2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM). 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM) 2023, 07-10 Mar 2023, Seoul, Korea. Institute of Electrical and Electronics Engineers , pp. 1-3. ISBN 9798350332520

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Item Type: Proceedings Paper
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© 2023 The Authors. Except as otherwise noted, this author-accepted version of a paper published in 2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM) 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: Reservoir computing; Solid electrolyte FET; Spoken-digit classification; Lyons passive ear model
Dates:
  • Published: 26 April 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 26 Feb 2024 15:36
Last Modified: 26 Feb 2024 15:36
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
Identification Number: 10.1109/edtm55494.2023.10103131
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