Journal
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume 59, Issue 3, Pages 1309-1316Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2010.2097254
Keywords
Analysis of nonlinear and nonstationary signals; EEG denoising; extrema and barycenters of oscillation; filter bank structure; Hurst exponent estimation; intrinsic mode functions; mono- and multivariate empirical mode decomposition; time varying representation
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Funding
- National Research Agengy (ANR) of France [mv-EMD BLAN07-0314-02]
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A novel empirical mode decomposition (EMD) algorithm, called 2T-EMD, for both mono- and multivariate signals is proposed in this correspondence. It differs from the other approaches by its computational lightness and its algorithmic simplicity. The method is essentially based on a redefinition of the signal mean envelope, computed thanks to new characteristic points, which offers the possibility to decompose multivariate signals without any projection. The scope of application of the novel algorithm is specified, and a comparison of the 2T-EMD technique with classical methods is performed on various simulated mono- and multivariate signals. The monovariate behaviour of the proposed method on noisy signals is then validated by decomposing a fractional Gaussian noise and an application to real life EEG data is finally presented.
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