The R Journal · 2009 · 131 citations · 5 references
EngineeringElectrical EngineeringBiomedical Signal ProcessingSpectroscopic AnalysisTime Series AnalysisDigital Signal ProcessingFrequency-domain AnalysisSignal ProcessingSpectral AnalysisSpectral TheoryTime-frequency AnalysisEmpirical Mode DecompositionPower Spectral AnalysisSpectral Feature ExtractionTime ScalesTime Series Spectral Analysis
The concept of empirical mode decomposition (EMD)and the Hilber tspectrum (HS) has been developed rapidly in many disciplines of science and engineering since Huang et al. (1998) invented EMD. The key feature of EMD is to decompose a signal into so-called intrinsic mode function (IMF). Further more, the Hilbert spectral analysis of intrinsic mode functions provides frequency information evolving with time and quantifies the amount of variation due to oscillation at different time scales and time locations. In this article,we introduce an R package called EMD (KimandOh, 2008) that performs one and two-dimensional EMD and HS.
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Norden E. Huang, Steven Long, Man‐Li C. Wu et al. · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 1998 · 23.3K citations · Full text
Computing, Computational Engineering, Biomedical Signal Processing +16
A simple boundary process technique for empirical mode decomposition
Kan Zeng, Mingxia He · 2004 · 41 citations