\(L_1\)-norm constraint kernel adaptive filtering framework for precise and robust indoor localization under the internet of things

DOI10.1016/j.ins.2021.12.026OpenAlexW4200303591MaRDI QIDQ6154779

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Publication date: 16 February 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2021.12.026

zbMATH Keywords

internet of thingsindoor localizationkernel adaptive filterabrupt noisepositioning accuracy

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Adaptive control/observation systems (93C40) Internet topics (68M11)

Cites Work

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• Volatility Modeling with a GeneralizedtDistribution
• Correntropy: Properties and Applications in Non-Gaussian Signal Processing
• The Kernel Least-Mean-Square Algorithm
• Online Prediction of Time Series Data With Kernels
• Generalized Correntropy for Robust<?Pub _newline ?>Adaptive Filtering
• The Kernel Recursive Least-Squares Algorithm

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