An adaptive data analysis method for nonlinear and nonstationary time series: The empirical mode decomposition and hilbert spectral analysis

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

28 Scopus citations

Abstract

An adaptive data analysis method, the Empirical Mode Decomposition and Hilbert Spectral Analysis, is introduced and reviewed briefly. The salient properties of the method is emphasized in this review; namely, physical meaningful adaptive basis, instantaneous frequency, and using intra-wave frequency modulation to represent nonlinear waveform distortion. This method can perform and enhance most of the traditional data analysis task such as filtering, regression, and spectral analysis adaptively. Also presented are the mathematical problems associated with the new method. It is hope that this presentation will entice the interest of the mathematical community to examine this empirically based method and inject mathematical rigor into the new approach.

Original languageEnglish
Title of host publicationApplied and Numerical Harmonic Analysis
PublisherSpringer International Publishing
Pages363-376
Number of pages14
Edition9783764377779
DOIs
StatePublished - 2007

Publication series

NameApplied and Numerical Harmonic Analysis
Number9783764377779
ISSN (Print)2296-5009
ISSN (Electronic)2296-5017

Fingerprint

Dive into the research topics of 'An adaptive data analysis method for nonlinear and nonstationary time series: The empirical mode decomposition and hilbert spectral analysis'. Together they form a unique fingerprint.

Cite this