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 :
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