Multivariate empirical mode decomposition and application to multichannel filtering

Julien Fleureau, Amar Kachenoura, Laurent Albera, Jean-Claude Nunes, Lotfi Senhadji
2011 Signal Processing  
Empirical Mode Decomposition (EMD) is an emerging topic in signal processing research, applied in various practical fields due in particular to its data-driven filter bank properties. In this paper, a novel EMD approach called X-EMD (eXtended-EMD) is proposed, which allows for a straightforward decomposition of mono-and multivariate signals without any change in the core of the algorithm. Qualitative results illustrate the good behavior of the proposed algorithm whatever the signal dimension
more » ... Moreover, a comparative study of X-EMD with classical mono-and multivariate methods is presented and shows its competitiveness. Besides, we show that X-EMD extends the filter bank properties enjoyed by monovariate EMD to the case of multivariate EMD. Finally, a practical application on multi-channel sleep recording is presented.
doi:10.1016/j.sigpro.2011.01.018 fatcat:hy63titl4zcttjbaimrr6omn3q