DocumentCode :
2618483
Title :
3A-EMD: A generalized approach for monovariate and multivariate EMD
Author :
Leureau, Julien F. ; Kachenoura, Amar ; Nunes, Jean-Claude ; Albera, Laurent ; Senhadji, Lotfi
Author_Institution :
UMR 642, Inserm, Rennes, France
fYear :
2010
fDate :
10-13 May 2010
Firstpage :
300
Lastpage :
303
Abstract :
EMD is an emerging topic in signal processing research and is applied in various practical fields. Its recent extension to multivariate signals, motivated by the need to jointly analyze multi-channel signals, is an active topic of research. However, all the existing etensions specifically hold either mono-, bi- or tri-variate signals or require multiple projections that complexity the original process. In this communication, a novel EMD approach called 3A-EMD is proposed. It is essentially based on the redefinition of the mean envelope operator and allows, under certain conditions, a straightforward decomposition of monovariate and multivariate signals without any change in the core of the algorithm. A comparative study with classical monovariate and bivariate methods is presented and shows the competitiveness of 3A-EMD. A trivariate decomposition is also given to illustrate the extension of the proposed algorithm to any signal dimension, D>2.
Keywords :
signal processing; 3A-EMD approach; empirical mode decomposition; monovariate EMD generalized approach; multichannel signal analysis; multivariate EMD generalized approach; multivariate signal decomposition; signal processing research; Artificial neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-7165-2
Type :
conf
DOI :
10.1109/ISSPA.2010.5605465
Filename :
5605465
Link To Document :
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