Title
Variable Kernel Width Algorithm of Generalized Maximum Correntropy Criteria for Censored Regression
Abstract
The constant kernel width of generalized maximum correntropy criteria (GMCC) has arisen that the steady-state error and convergence speed can be mutually exclusive. To solve this problem, this brief proposes the variable kernel width (VKW) GMCC algorithm. Actually, due to the censored problem, the output data value beyond the limit of the recording device can not be well observed. In this case, we further developed a variable kernel width GMCC algorithm based on censored regression (CR-VKWGMCC). Simulation results show that the proposed CR-VKWGMCC algorithm has excellent performance in both Gaussian and non Gaussian noise.
Year
DOI
Venue
2022
10.1109/TCSII.2021.3103504
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
Keywords
DocType
Volume
Signal processing algorithms, Kernel, Steady-state, Filtering algorithms, Convergence, Adaptive filters, Optimized production technology, Generalized maximum correntropy criteria, variable kernel width, censored regression, adaptive filtering
Journal
69
Issue
ISSN
Citations 
3
1549-7747
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Haiquan Zhao100.68
Bing Chen200.34
Yingying Zhu301.01
Xiaoqiong He400.68
Zeliang Shu5567.71