An Alternative Formulation for the Empirical Mode Decomposition

Thomas Oberlin (1) , Sylvain Meignen (1) , Valérie Perrier (1)

1 MGMI - Modélisation Géométrique & Multirésolution pour l'Image

Empirical Mode Decomposition (EMD) is a relatively new method for adaptive multiscale signal representation. As it allows to adaptively analyze nonlinear and non-stationary signals, it is widely used in signal processing. Yet, as the standard EMD method lacks a solid mathematical background, many alternative constructions have been proposed to define similar decompositions in a more comprehensive way. This paper is in line with this idea, as it defines a new decomposition that lies on direct constrained optimization. We show that this new approach gives satisfactory results for narrow-band signals and preserves the essential characteristics of the original EMD

Mots clés: Empirical Mode Decomposition; Constrained B-splines; Adaptive signal decomposition; Adaptive multiscale analysis

Domaines: Recherche d'information [cs.IR]

Thomas Oberlin, Sylvain Meignen, Valérie Perrier. An Alternative Formulation for the Empirical Mode Decomposition. IEEE Transactions on Signal Processing, 2012, 60 (5), pp.2236-2246. ⟨10.1109/TSP.2012.2187202⟩. ⟨hal-00553107⟩