DocumentCode
177513
Title
On selecting relevant intrinsic mode functions in empirical mode decomposition: An energy-based approach
Author
Baptista de Souza, Douglas ; Chanussot, Jocelyn ; Favre, Anne-Catherine
Author_Institution
GIPSA-Lab., Domaine Univ., St. Martin d´Hères, France
fYear
2014
fDate
4-9 May 2014
Firstpage
325
Lastpage
329
Abstract
Although the empirical mode decomposition is a powerful tool for analyzing complicated datasets, many irrelevant intrinsic mode functions may appear in the decomposition. In this paper, we develop an energy-based method to detect relevant intrinsic mode functions. The new method can be seen as a generalization of techniques that are based on correlation. An experimental study is carried out in different datasets for assessing the performance of the proposed technique.
Keywords
signal classification; signal processing; complicated dataset analysis; correlation technique; empirical mode decomposition; energy based method; relevant intrinsic mode functions; Correlation; Empirical mode decomposition; Mutual information; Signal processing; Time series analysis; Time-frequency analysis; Wavelet transforms; correlation; empirical mode decomposition; energy; intrinsic mode function; mutual information;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6853611
Filename
6853611
Link To Document