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Nonstationary signal analysis based on EMD and extremum points
JIAN-JIA PAN1; YUAN-YAN TANG2
2012-10-29
Conference Name2012 International Conference on Wavelet Analysis and Pattern Recognition
Source PublicationProceedings of the 2012 International Conference on Wavelet Analysis and Pattern Recognition
Pages260-265
Conference Date15-17 July 2012
Conference PlaceXian
CountryChina
Abstract

Empirical mode decomposition (EMD) is a data driven processing algorithm, which has no predetermined filter. It is able to perfectly analyze the nonlinear and nonstationary signals. In EMD decomposition processing, the envelopes are computed by spline interpolation, which is time-consuming. In this work, firstly, we proposed a boundary extending method based on linear prediction and boundary extreme points adjusting, which reduce the end effects problem. And then, based on the straight line method, we proposed just using the extrema points to detect the extrema information about the signal, which is Extrema Points Empirical Mode Decomposition (EPEMD). By using the extrema points information, a fast and distinct frequency change detection method is proposed. 

KeywordBoundary Extending Emd Extrema Points Time-frequency Analysis
DOI10.1109/ICWAPR.2012.6294789
URLView the original
Language英語English
Scopus ID2-s2.0-84867794995
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Citation statistics
Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Department of Computer Science, Hong Kong Baptist University, Hong Kong
2.Department of Computer Science, Hong Kong Baptist University, Hong Kong
Recommended Citation
GB/T 7714
JIAN-JIA PAN,YUAN-YAN TANG. Nonstationary signal analysis based on EMD and extremum points[C], 2012, 260-265.
APA JIAN-JIA PAN., & YUAN-YAN TANG (2012). Nonstationary signal analysis based on EMD and extremum points. Proceedings of the 2012 International Conference on Wavelet Analysis and Pattern Recognition, 260-265.
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