Complex Correntropy with Variable Center: Definition, Properties, and Application to Adaptive Filtering

The complex correntropy has been successfully applied to complex domain adaptive filtering, and the corresponding maximum complex correntropy criterion (MCCC) algorithm has been proved to be robust to non-Gaussian noises. However, the kernel function of the complex correntropy is usually limited to...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Entropy (Basel, Switzerland) Jg. 22; H. 1; S. 70
Hauptverfasser: Dong, Fei, Qian, Guobing, Wang, Shiyuan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland MDPI AG 06.01.2020
MDPI
Schlagworte:
Adaptive filters
Algorithms
complex
Cost function
Criteria
Domains
emse
Kernel functions
mccc-vc
Mean square errors
Noise
Optimization
Performance enhancement
Signal processing
stability
Steady state
variable center
Variables
EMSE
stability
MCCC-VC
complex
variable center
ISSN:1099-4300, 1099-4300
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The complex correntropy has been successfully applied to complex domain adaptive filtering, and the corresponding maximum complex correntropy criterion (MCCC) algorithm has been proved to be robust to non-Gaussian noises. However, the kernel function of the complex correntropy is usually limited to a Gaussian function whose center is zero. In order to improve the performance of MCCC in a non-zero mean noise environment, we firstly define a complex correntropy with variable center and provide its probability explanation. Then, we propose a maximum complex correntropy criterion with variable center (MCCC-VC), and apply it to the complex domain adaptive filtering. Next, we use the gradient descent approach to search the minimum of the cost function. We also propose a feasible method to optimize the center and the kernel width of MCCC-VC. It is very important that we further provide the bound for the learning rate and derive the theoretical value of the steady-state excess mean square error (EMSE). Finally, we perform some simulations to show the validity of the theoretical steady-state EMSE and the better performance of MCCC-VC.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1099-4300
1099-4300
DOI:10.3390/e22010070