Abstract
Based on numerical experiments on white noise using the empirical mode decomposition (EMD) method, we find empirically that the EMD is effectively a dyadic filter, the intrinsic mode function (IMF) components are all normally distributed, and the Fourier spectra of the IMF components are all identical and cover the same area on a semi–logarithmic period scale. Expanding from these empirical findings, we further deduce that the product of the energy density of IMF and its corresponding averaged period is a constant, and that the energy–density function is chi–squared distributed. Furthermore, we derive the energy–density spread function of the IMF components. Through these results, we establish a method of assigning statistical significance of information content for IMF components from any noisy data. Southern Oscillation Index data are used to illustrate the methodology developed here.
Keywords
Hilbert–Huang transformLogarithmMode (computer interface)White noiseFilter (signal processing)Noise (video)Function (biology)MathematicsSpectral densityProbability density functionEnergy (signal processing)StatisticsFourier transformStatistical physicsMathematical analysisPhysicsComputer scienceArtificial intelligence
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Publication Info
- Year
- 2004
- Type
- article
- Volume
- 460
- Issue
- 2046
- Pages
- 1597-1611
- Citations
- 1688
- Access
- Closed
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Cite This
Zhaohua Wu,
Norden E. Huang
(2004).
A study of the characteristics of white noise using the empirical mode decomposition method.
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
, 460
(2046)
, 1597-1611.
https://doi.org/10.1098/rspa.2003.1221
Identifiers
- DOI
- 10.1098/rspa.2003.1221