AE-BiLSTM: Multivariate Time-Series EMI Anomaly Detection in 5G-R High-Speed Rail Wireless Communications

Fan, Y. orcid.org/0000-0001-8038-7337, Zhang, L. orcid.org/0000-0002-4535-3200 and Li, K. (2024) AE-BiLSTM: Multivariate Time-Series EMI Anomaly Detection in 5G-R High-Speed Rail Wireless Communications. In: 2024 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE ICC 2024 Workshop On Machine Learning And Deep Learning For Wireless Security, 09 Jun 2024, Denver, CO, USA. IEEE , pp. 439-444. ISBN 979-8-3503-0406-0

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Item Type: Proceedings Paper
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Keywords: Anomaly Detection, Electromagnetic Interference, Deep Learning, High-Speed Rail Wireless Communications
Dates:
  • Published: 12 August 2024
  • Published (online): 12 August 2024
  • Accepted: 14 March 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds)
The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 05 Apr 2024 14:20
Last Modified: 13 Sep 2024 14:54
Published Version: https://ieeexplore.ieee.org/document/10615719
Status: Published
Publisher: IEEE
Identification Number: 10.1109/ICCWorkshops59551.2024.10615719
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