Bias-compensated affine-projection-like algorithm based on maximum correntropy criterion for robust filtering

DOI10.1016/J.JFRANKLIN.2021.12.018zbMath1483.93670OpenAlexW4200040213WikidataQ123024155 ScholiaQ123024155MaRDI QIDQ2667434

Xiaoqiong He, Haiquan Zhao, Wang Xiang

Publication date: 4 March 2022

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.12.018

zbMATH Keywords

robust adaptive filteringmaximum correntropy algorithm

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Identification in stochastic control theory (93E12) Stochastic learning and adaptive control (93E35)

Cites Work

• Unnamed Item
• Unnamed Item
• Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments
• Variable Explicit Regularization in Affine Projection Algorithm: Robustness Issues and Optimal Choice
• Generalized Correntropy for Robust<?Pub _newline ?>Adaptive Filtering
• On the Convergence Behavior of the Affine Projection Algorithm for Adaptive Filters
• Bias-Compensated Sign Algorithm for Noisy Inputs and Its Step-Size Optimization
• Widely Linear Complex-Valued Estimated-Input LMS Algorithm for Bias-Compensated Adaptive Filtering With Noisy Measurements
• Consistent normalized least mean square filtering with noisy data matrix

This page was built for publication: Bias-compensated affine-projection-like algorithm based on maximum correntropy criterion for robust filtering