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A New Wavelet-Based Mode Decomposition for Oscillating Signals and Comparison with the Empirical Mode Decomposition

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Information Technology: New Generations

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 448))

Abstract

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.

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Author information

Authors and Affiliations

  1. Department of Mathematics (B37), University of Liège, Allée de la découverte 12, 4000, Liège, Belgium

    Adrien Deliège & Samuel Nicolay

Authors
  1. Adrien Deliège
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  2. Samuel Nicolay
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Corresponding author

Correspondence to Adrien Deliège .

Editor information

Editors and Affiliations

  1. PHASE , Las Vegas, Nevada, USA

    Shahram Latifi

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© 2016 Springer International Publishing Switzerland

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Deliège, A., Nicolay, S. (2016). A New Wavelet-Based Mode Decomposition for Oscillating Signals and Comparison with the Empirical Mode Decomposition. In: Latifi, S. (eds) Information Technology: New Generations. Advances in Intelligent Systems and Computing, vol 448. Springer, Cham. https://doi.org/10.1007/978-3-319-32467-8_83

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  • DOI: https://doi.org/10.1007/978-3-319-32467-8_83

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32466-1

  • Online ISBN: 978-3-319-32467-8

  • eBook Packages: EngineeringEngineering (R0)

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