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...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on signal processing 2012-05, Vol.60 (5), p.2236-2246
Main Authors: Oberlin, T., Meignen, S., Perrier, V.
Format: Article
Language:English
Subjects:
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
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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