Correntropy as a novel similarity metric

DMA, FCUP, Room 0.31
Friday, 13 March, 2009 - 13:00

Abstract

The concept of similarity is crucial in statistical thinking, although most often we translate it in terms of second order moments of the PDF. Correntropy is motivated through entropy which also quantifies the shape of the PDF. Properties of correntropy will be presented, as well as applications to real world problems. The Seminar will end with a set of open questions.

References

Jeong K-H, Liu W., Principe J., “The correntropy MACE filter”, Pattern Recognition Volume 42, Issue 5,pp 871-885.
Xu J., Principe J., “A Pitch Detector Based on a Generalized Correlation Function”, IEEE Trans. on Audio, Speech and Language Processing, Volume 16, Issue 8, Nov. 2008 Page(s):1420 – 1432.
Xu J., Bakardjian H., Cichocki A., and Principe J., “A New Nonlinear Similarity Measure for Multichannel Signals”, Neural Networks (invited paper), Volume 21, Issues 2-3, March-April 2008, Pages 222-231.
Liu W., Pokharel P., Principe J., “Correntropy: Properties and Applications in Non Gaussian Signal Processing”, IEEE Trans. Sig. Proc., vol 55; # 11, pages 5286-5298, 2007.
Santamaria I., Pokharel P., Principe J., “Generalized Correlation Function: Definition, Properties and Application to Blind Equalization”, IEEE Trans. Signal Proc. vol 54, no 6, pp 2187- 2186, 2006.

Speaker: 

Jose C. Principe, Ph.D., University of Florida, USA