2008 Special Issue: A new nonlinear similarity measure for multichannel signals

Authors:
Jian-Wu Xu;Hovagim Bakardjian;Andrzej Cichocki;Jose C. Principe
Affiliations:
Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA;Advanced Brain Signal Processing, RIKEN Brain Science Institute, Wako-shi, Saitama, 351-0198, Japan;Advanced Brain Signal Processing, RIKEN Brain Science Institute, Wako-shi, Saitama, 351-0198, Japan;Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA
Venue:
Neural Networks
Year:
2008

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Abstract

We propose a novel similarity measure, called the correntropy coefficient, sensitive to higher order moments of the signal statistics based on a similarity function called the cross-correntopy. Cross-correntropy nonlinearly maps the original time series into a high-dimensional reproducing kernel Hilbert space (RKHS). The correntropy coefficient computes the cosine of the angle between the transformed vectors. Preliminary experiments with simulated data and multichannel electroencephalogram (EEG) signals during behaviour studies elucidate the performance of the new measure versus the well-established correlation coefficient.