Paper Info
Title
Noise-Free Maximum Correntropy Criterion Algorithm In Non-Gaussian Environment
Abstract
In this brief, a noise-free maximum correntropy criterion (NFMCC) algorithm is proposed for system identification in non-Gaussian environments. The proposed algorithm utilizes correntropy theory to construct a cost function which is realized based on a normalized Gaussian kernel. In addition, a new dynamic step size scheme is proposed to enhance the performance of the proposed algorithm, which is implemented by minimizing the noise-free a posteriori error signal, and the mean square deviation (MSD) is greatly decreased. The proposed NFMCC algorithm shows significant property in reducing the detrimental effects of outliers and impulsive noise with different input signals. Moreover, a Students' T distributed noise is employed to evaluate the effectiveness of the proposed algorithm in terms of the MSD and convergence for heavy tailed noising environment. The parameter effects on the NFMCC algorithm are also presented, and its performance is investigated on a real-life channel that is measured in underwater. Simulation results prove the effectiveness of the proposed algorithm which provides a considerable computational complexity and an acceptable running time.
Year
DOI
Venue
2020
10.1109/TCSII.2019.2914511
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
Keywords
DocType
Volume
Heuristic algorithms, Signal processing algorithms, Cost function, Computational complexity, Kernel, Noise reduction, Circuits and systems, Adaptive filters, noise-free algorithm, maximum correntropy criterion, Students' T distribution
Journal
67
Issue
ISSN
Citations 
10
1549-7747
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Wanlu Shi113.73
Yingsong Li212034.72
Yanyan Wang3218.87