Treffer: Empirical mode decomposition revisited by multicomponent non-smooth convex optimization

Title:
Empirical mode decomposition revisited by multicomponent non-smooth convex optimization
Authors:
PUSTELNIK, Nelly, BORGNAT, Pierre, FLANDRIN, Patrick
Source:
Signal processing. 102:313-331
Publisher Information:
Amsterdam: Elsevier, 2014.
Publication Year:
2014
Physical Description:
print, 64 ref
Original Material:
INIST-CNRS
Subject Terms:
Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Signal, bruit, Signal, noise, Détection, estimation, filtrage, égalisation, prédiction, Detection, estimation, filtering, equalization, prediction, Algorithme, Algorithm, Algoritmo, Etat actuel, State of the art, Estado actual, Evaluation performance, Performance evaluation, Evaluación prestación, Flexibilité, Flexibility, Flexibilidad, Interpolation, Interpolación, Méthode décomposition, Decomposition method, Método descomposición, Méthode empirique, Empirical method, Método empírico, Méthode itérative, Iterative method, Método iterativo, Performance algorithme, Algorithm performance, Resultado algoritmo, Programmation convexe, Convex programming, Programación convexa, Programmation non convexe, Non convex programming, Programación no convexa, Taux convergence, Convergence rate, Relación convergencia, Traitement signal, Signal processing, Procesamiento señal, Convex optimization, Empirical Mode Decomposition (EMD), Intrinsic mode functions (IMF), Proximal algorithms, Trend-fluctuation, ℓp-norm
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Laboratoire de Physique, ENS de Lyon, CNRS, Université Claude Bernard Lyon 1, Université de Lyon, UMR CNRS 5672, 69364 Lyon, France
ISSN:
0165-1684
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28481487
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.28481487
Database:
PASCAL Archive

Weitere Informationen

This work deals with the decomposition of a signal into a collection of intrinsic mode functions. More specifically, we aim to revisit Empirical Mode Decomposition (EMD) based on a sifting process step, which highly depends on the choice of an interpolation method, the number of inner iterations, and that does not have any convergence guarantees. The proposed alternative to the sifting process is based on non-smooth convex optimization allowing to integrate flexibility in the criterion we aim to minimize. We discuss the choice of the criterion, we describe the proposed algorithm and its convergence guarantees, we propose an extension to deal with multivariate signals, and we figure out the effectiveness of the proposed method compared to the state-of-the-art.