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A novel formulation of independence detection based on the sample characteristic function

Author
De Cabrera, F.; Riba, J.
Type of activity
Presentation of work at congresses
Name of edition
26th European Signal Processing Conference
Date of publication
2018
Presentation's date
2018-09-03
Book of congress proceedings
EUSIPCO 2018: 26th European Signal Processing Conference: Rome, Italy: September 3-7, 2018
First page
2608
Last page
2612
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
10.23919/EUSIPCO.2018.8553062
Repository
http://hdl.handle.net/2117/186732 Open in new window
URL
https://ieeexplore.ieee.org/document/8553062 Open in new window
Abstract
A novel independence test for continuous random sequences is proposed in this paper. The test is based on seeking for coherence in a particular fixed-dimension feature space based on a uniform sampling of the sample characteristic function of the data, providing significant computational advantages over kernel methods. This feature space relates uncorrelation and independence, allowing to analyze the second order statistics as it is encountered in traditional signal processing. As a result, the ...
Citation
De Cabrera, F.; Riba, J. A novel formulation of independence detection based on the sample characteristic function. A: European Signal Processing Conference. "EUSIPCO 2018: 26th European Signal Processing Conference: Rome, Italy: September 3-7, 2018". Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 2608-2612.
Keywords
Correlation, Europe Coherence., Kernel, Probability density function, Random variables, Signal processing
Group of research
SPCOM - Signal Processing and Communications Group

Participants