Wang, S. orcid.org/0000-0002-9426-0174, Du, X. and Deng, T. orcid.org/0000-0003-4507-5746 (2023) A zeroing neurodynamics‐based location method for nodes in underwater acoustic sensor network. CAAI Transactions on Intelligence Technology, 8 (3). pp. 661-669. ISSN 2468-2322
Abstract
Zeroing neurodynamics methodology, which dedicates to finding equilibrium points of equations, has been proven to be a powerful tool in the online solving of problems with considerable complexity. In this paper, a method for underwater acoustic sensor network (UASN) localisation is proposed based on zeroing neurodynamics methodology to preferably locate moving underwater nodes. A zeroing neurodynamics model specifically designed for UASN localisation is constructed with rigorous theoretical analyses of its effectiveness. The proposed zeroing neurodynamics model is compatible with some localisation algorithms, which can be utilised to eliminate error in non-ideal situations, thus further improving its effectiveness. Finally, the effectiveness and compatibility of the proposed zeroing neurodynamics model are substantiated by examples and computer simulations.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. https://creativecommons.org/licenses/by-nc-nd/4.0/ |
Keywords: | artificial neural network; internet of things; underwater acoustic sensor network |
Dates: |
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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: | 16 May 2023 15:53 |
Last Modified: | 01 Oct 2024 14:34 |
Status: | Published |
Publisher: | Institution of Engineering and Technology (IET) |
Refereed: | Yes |
Identification Number: | 10.1049/cit2.12225 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:199196 |