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On the Confidence Limit of Hilbert SpectrumConfidence limit is a routine requirement for Fourier spectral analysis. But this confidence limit is established based on ergodic theory: For stationary process, temporal average equals the ensemble average. Therefore, one can divide the data into n-sections and treat each section as independent realization. Most natural processes in general, and climate data in particular, are not stationary; therefore, there is a need for the Hilbert Spectral analysis for such processes. Here ergodic theory is no longer applicable. We propose to use various adjustable parameters in the shifting processes of the Empirical Mode Decomposition (EMD) method to obtain an ensemble of Intrinsic Mode Function 0 sets. Based on such an ensemble, we introduce a statistical measure in. a form of confidence limits for the Intrinsic Mode Functions, and consequently, the Hilbert spectra. The criterion of selecting the various adjustable parameters is based on the orthogonality test of the resulting M F sets. Length-of-day data from 1962 to 2001 will be used to illustrate this new approach. Its implication in climate data analysis will also be discussed.
Document ID
20040013036
Acquisition Source
Goddard Space Flight Center
Document Type
Conference Paper
Authors
Huang, Norden
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 21, 2013
Publication Date
January 1, 2003
Subject Category
Numerical Analysis
Meeting Information
Meeting: Joint SIAM-CAIMS Meeting
Location: Montreal
Country: Canada
Start Date: June 16, 2003
End Date: June 20, 2003
Sponsors: Canadian Applied and Industrial Mathematics Society, Society for Industrial and Applied Mathematics
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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