@inproceedings{a927312995bd42ffa10afbff075d2710,
title = "Diffusion generalized spline nonlinear adaptive filters under Maximum Correntropy Criterion",
abstract = "Due to complex nonlinearities in general, linear adaptive filter is not suitable, the nonlinear adaptive filter using splines based on minimum mean square error criteria is proposed to identificate nonlinear systems in additive Gaussain noise environment. To address the issues of the more general nonlinear system structure and the addictive non-Gaussain noise environments disturbance, this paper proposes generalized spline nonlinear adaptive filters under maximum correntropy criterion (GSNAF-MCC). Meanwhile, GSNAF-MCC is extended to diffusion networks, resulting in the diffusion GSNAF-MCC (D-GSNAF-MCC). The proposed D-GSNAF-MCC decreases the steady-state error and improves the convergence speed. The simulations demonstrate that the proposed algorithms have better performance compared with related SAFs algorithms.",
keywords = "Adaptive filters, Diffusion, MCC, Non-Gaussain noise, Nonlinear system identification, Spline functions",
author = "Chuang Liu and Lijuan Jia and Deshui Miao",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 China Automation Congress, CAC 2021 ; Conference date: 22-10-2021 Through 24-10-2021",
year = "2021",
doi = "10.1109/CAC53003.2021.9727397",
language = "English",
series = "Proceeding - 2021 China Automation Congress, CAC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4299--4304",
booktitle = "Proceeding - 2021 China Automation Congress, CAC 2021",
address = "United States",
}