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A New Wavelet-Based Mode Decomposition for Oscillating Signals and Comparison with the Empirical Mode Decomposition
Deliège, Adrien; Nicolay, Samuel
2016In Information Technology: New Generations
Peer reviewed
 

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Keywords :
wavelet; mode decomposition; EMD
Abstract :
[en] We introduce a new method based on wavelets (EWMD) for decomposing a signal into quasi-periodic oscillating components with smooth time-varying amplitudes. This method is inspired by both the “classic” wavelet-based decomposition and the empirical mode decomposition (EMD). We compare the reconstruction skills and the period detection ability of the method with the well-established EMD on toys examples and the ENSO climate index. It appears that the EWMD accurately decomposes and reconstructs a given signal (with the same efficiency as the EMD), it is better at detecting prescribed periods and is less sensitive to noise. This work provides the first version of the EWMD. Even though there is still room for improvement, it turns out that preliminary results are highly promising.
Disciplines :
Mathematics
Author, co-author :
Deliège, Adrien ;  Université de Liège > Département de mathématique > Analyse - Analyse fonctionnelle - Ondelettes
Nicolay, Samuel  ;  Université de Liège > Département de mathématique > Analyse - Analyse fonctionnelle - Ondelettes
Language :
English
Title :
A New Wavelet-Based Mode Decomposition for Oscillating Signals and Comparison with the Empirical Mode Decomposition
Publication date :
April 2016
Event name :
13th International Conference on Information Technology : New Generations
Event place :
Las Vegas, United States - Nevada
Event date :
April 11-13, 2016
Audience :
International
Main work title :
Information Technology: New Generations
Publisher :
Springer, Switzerland
ISBN/EAN :
978-3-319-32467-8
Collection name :
Advances in Intelligent Systems and Computing 448
Pages :
959-968
Peer reviewed :
Peer reviewed
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
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