DocumentCode
2778742
Title
Correntropy: A Localized Similarity Measure
Author
Liu, Weifeng ; Pokharel, P.P. ; Principe, J.C.
Author_Institution
Univ. of Florida, Gainesville
fYear
0
fDate
0-0 0
Firstpage
4919
Lastpage
4924
Abstract
The measure of similarity normally utilized in statistical signal processing is based on second order moments. In this paper, we reveal the probabilistic meaning of correntropy as a new localized similarity measure based on information theoretic learning (ITL) and kernel methods. As such it has vastly different properties when compared with mean square error (MSE) that can be very useful in nonlinear, non-Gaussian signal processing. Two examples are presented to illustrate the technique.
Keywords
learning (artificial intelligence); mean square error methods; signal processing; correntropy; information theoretic learning; kernel methods; localized similarity measure; mean square error; nonGaussian signal processing; second order moments; statistical signal processing; Autocorrelation; Bandwidth; Electric variables control; Entropy; Kernel; Mean square error methods; Random processes; Random variables; Signal processing; Yield estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9490-9
Type
conf
DOI
10.1109/IJCNN.2006.247192
Filename
1716783
Link To Document