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Méthodes de traitement du signal par décomposition en modes empiriques

Abstract : This document aims at presenting, assessing and comparing several signal analysis techniques relying on the empirical mode decomposition. This adaptive method, developed by Huang, is is frequently used for the analysis of nonlinear signals, i.e. signals stemming from nonlinear systems. One weakness of the method lies in its lack of theoretical foundation, though it should be mentioned that some authors attempted to make a more mathematical presentation of the method. Nonetheless, the EMD has been applied for a large variety of applications---such as industrial machines monitoring and medical signals analysis to name a few. The EMD is the cornerstone of increasingly popular signal analysis techniques such as the local mean decomposition and the Hilbert-Huang Transform. These methods are detailed in this note along with the associated Python implementation that is freely downloadable with this document.
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Contributor : Alain Batailly Connect in order to contact the contributor
Submitted on : Wednesday, June 20, 2018 - 6:21:18 PM
Last modification on : Sunday, October 25, 2020 - 4:29:21 AM


Distributed under a Creative Commons Attribution 4.0 International License


  • HAL Id : hal-01819670, version 1



Nicolas Di Palma, Alain Batailly, Mathias Legrand. Méthodes de traitement du signal par décomposition en modes empiriques. [Rapport de recherche] Université McGill. 2018. ⟨hal-01819670⟩



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