On the Application of a Sparse Data Observers (SDOs) Outlier Detection Algorithm to Mitigate Poisoning Attacks in UltraWideBand (UWB) Line-of-Sight (LOS)/Non-Line-of-Sight (NLOS) Classification

On the Application of a Sparse Data Observers (SDOs) Outlier Detection Algorithm to Mitigate Poisoning Attacks in UltraWideBand (UWB) Line-of-Sight (LOS)/Non-Line-of-Sight (NLOS) Classification

The classification of the wireless propagation channel between Line-of-Sight (LOS) or Non-Line-of-Sight (NLOS) is useful in the operation of wireless communication systems. The research community has increasingly investigated the application of machine learning (ML) to LOS/NLOS classification and th...

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Bibliographic Details
Main Author: Gianmarco Baldini
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Future Internet
Subjects:
security
wireless communication
deep learning
machine learning
Online Access:https://www.mdpi.com/1999-5903/17/2/60
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https://www.mdpi.com/1999-5903/17/2/60

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