An Alternative Formulation for the Empirical Mode Decomposition

The Empirical Mode Decomposition (EMD) is a relatively new adaptive method for multicomponent signal representation which allows for analyzing nonlinear and nonstationary signals. In spite of its lack of mathematical foundations, very few papers are dedicated to defining new decompositions that woul...

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Veröffentlicht in:	IEEE transactions on signal processing 2012-05, Vol.60 (5), p.2236-2246
Hauptverfasser:	Oberlin, T., Meignen, S., Perrier, V.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive signal decomposition Applied sciences Computer Science constrained optimization Context Decomposition Detection, estimation, filtering, equalization, prediction Educational institutions Electronic mail Empirical analysis empirical mode decomposition (EMD) Exact sciences and technology Foundations Information Retrieval Information, signal and communications theory Mathematical analysis Nonlinearity Optimization Polynomials Preserves Representations Signal and communications theory Signal representation. Spectral analysis Signal resolution Signal, noise Splines (mathematics) Telecommunications and information theory
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Beschreibung
Zusammenfassung:	The Empirical Mode Decomposition (EMD) is a relatively new adaptive method for multicomponent signal representation which allows for analyzing nonlinear and nonstationary signals. In spite of its lack of mathematical foundations, very few papers are dedicated to defining new decompositions that would preserve the interesting properties of the EMD while improving the mathematical setting. The new decomposition based on direct constrained optimization we introduce in this article is an attempt in that direction.
ISSN:	1053-587X 1941-0476
DOI:	10.1109/TSP.2012.2187202