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Decomposing non-stationary signals with time-varying wave-shape functions

Publication ,  Journal Article
Colominas, MA; Wu, HT
Published in: IEEE Transactions on Signal Processing
January 1, 2021

Modern time series are usually composed of multiple oscillatory components, with time-varying frequency and amplitude contaminated by noise. The signal processing mission is further challenged if each component has an oscillatory pattern, or the wave-shape function, far from a sinusoidal function, and the oscillatory pattern is even changing from time to time. In practice, if multiple components exist, it is desirable to robustly decompose the signal into each component for various purposes, and extract desired dynamics information. Such challenges have raised a significant amount of interest in the past decade, but a satisfactory solution is still lacking. We propose a novel nonlinear regression scheme to robustly decompose a signal into its constituting multiple oscillatory components with time-varying frequency, amplitude and wave-shape function. We coined the algorithm shape-adaptive mode decomposition (SAMD). In addition to simulated signals, we apply SAMD to two physiological signals, impedance pneumography and electroencephalography. Comparison with existing solutions, including linear regression, recursive diffeomorphism-based regression and multiresolution mode decomposition, shows that our proposal can provide an accurate and meaningful decomposition with computational efficiency.

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Published In

IEEE Transactions on Signal Processing

DOI

EISSN

1941-0476

ISSN

1053-587X

Publication Date

January 1, 2021

Volume

69

Start / End Page

5094 / 5104

Related Subject Headings

  • Networking & Telecommunications
 

Citation

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Colominas, M. A., & Wu, H. T. (2021). Decomposing non-stationary signals with time-varying wave-shape functions. IEEE Transactions on Signal Processing, 69, 5094–5104. https://doi.org/10.1109/TSP.2021.3108678
Colominas, M. A., and H. T. Wu. “Decomposing non-stationary signals with time-varying wave-shape functions.” IEEE Transactions on Signal Processing 69 (January 1, 2021): 5094–5104. https://doi.org/10.1109/TSP.2021.3108678.
Colominas MA, Wu HT. Decomposing non-stationary signals with time-varying wave-shape functions. IEEE Transactions on Signal Processing. 2021 Jan 1;69:5094–104.
Colominas, M. A., and H. T. Wu. “Decomposing non-stationary signals with time-varying wave-shape functions.” IEEE Transactions on Signal Processing, vol. 69, Jan. 2021, pp. 5094–104. Scopus, doi:10.1109/TSP.2021.3108678.
Colominas MA, Wu HT. Decomposing non-stationary signals with time-varying wave-shape functions. IEEE Transactions on Signal Processing. 2021 Jan 1;69:5094–5104.

Published In

IEEE Transactions on Signal Processing

DOI

EISSN

1941-0476

ISSN

1053-587X

Publication Date

January 1, 2021

Volume

69

Start / End Page

5094 / 5104

Related Subject Headings

  • Networking & Telecommunications