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Correntropy: Properties and Applications in Non-Gaussian Signal Processing.
- Source :
- IEEE Transactions on Signal Processing; Nov2007, Vol. 55 Issue 11, p5286-5298, 13p
- Publication Year :
- 2007
-
Abstract
- The optimality of second-order statistics depends heavily on the assumption of Gaussianity. In this paper, we elucidate further the probabilistic and geometric meaning of the recently defined correntropy function as a localized similarity mea- sure. A close relationship between correntropy and M-estimation is established. Connections and differences between correntropy and kernel methods are presented. As such correntropy has vastly different properties compared with second-order statistics that can be very useful in non-Gaussian signal processing, especially in the impulsive noise environment. Examples are presented to illustrate the technique. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1053587X
- Volume :
- 55
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 27420072
- Full Text :
- https://doi.org/10.1109/TSP.2007.896065