A substrate-independent framework to characterize reservoir computers

Dale, Matthew, Miller, Julian Francis orcid.org/0000-0002-7692-9655, Stepney, Susan orcid.org/0000-0003-3146-5401 et al. (1 more author) (2019) A substrate-independent framework to characterize reservoir computers. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 20180723. ISSN 1364-5021

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2019 The Authors.
Keywords: unconventional computing, evolution in materio, reservoir computing, Carbon Nanotubes (CNTs), Characterization, Physical computation, Reservoir computing
Dates:
  • Accepted: 15 May 2019
  • Published (online): 19 June 2019
  • Published: 28 June 2019
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Electronic Engineering (York)
The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Pure (York)
Date Deposited: 23 May 2019 09:40
Last Modified: 06 Dec 2023 13:07
Published Version: https://doi.org/10.1098/rspa.2018.0723
Status: Published
Refereed: Yes
Identification Number: https://doi.org/10.1098/rspa.2018.0723
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Filename: 1810.07135.pdf

Description: 1810.07135

Licence: CC-BY 2.5

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