An improved empirical mode decomposition based on combining extrapolating extrema with mirror extension

2006 ◽  
Author(s):  
Duanhui Duan ◽  
Qiusheng Wang
Keyword(s):  
Empirical Mode Decomposition ◽  
Mode Decomposition ◽  
Mirror Extension

BOUNDARY EXTENSION AND STOP CRITERIA FOR EMPIRICAL MODE DECOMPOSITION

2010 ◽  
Vol 02 (02) ◽  
pp. 157-169 ◽  
Author(s):  
QIN WU ◽  
SHERMAN D. RIEMENSCHNEIDER
Keyword(s):  
Empirical Mode Decomposition ◽  
Numerical Experiments ◽  
Boundary Extension ◽  
B Spline ◽  
Mode Decomposition ◽  
Mirror Extension

In this paper, a new idea about the boundary extension has been introduced and applied to the Empirical Mode Decomposition (EMD) algorithm. Instead of the traditional mirror extension on the boundary, we propose a ratio extension on the boundary. We also adopt the stop criteria by Rilling et al. for B-Spline based EMD algorithm. Numerical experiments are used for empirically assessing performance of the modified EMD algorithm. The examples indicate that the ratio boundary extension indeed improves the result of the original EMD.

END EFFECTS MITIGATION FOR EMPIRICAL MODE DECOMPOSITION WITH NONLINEAR GRAY MODEL

2012 ◽  
Vol 04 (01n02) ◽  
pp. 1250002 ◽  
Author(s):  
ZHI HE ◽  
YI SHEN ◽  
QIANG WANG ◽  
YAN WANG
Keyword(s):  
Empirical Mode Decomposition ◽  
Mirror Symmetry ◽  
Real Data ◽  
Data Series ◽  
Gray Model ◽  
End Effects ◽  
Synthetic Signal ◽  
Novel Approach ◽  
Mode Decomposition ◽  
Mirror Extension

To mitigate end effects of empirical mode decomposition (EMD), a novel approach inspired by the nonlinear gray model (GM) termed as GM(1,1,α) is presented. Other than traditional linear or mirror extension on the boundary, the GM(1,1,α) model is applied to predict two extrema at both ends of the data. It is worth noting that our GM(1,1,α) model is particularly useful for predicting uncertainty data. According to numerical experiments on synthetic signal as well as real data series, the proposed method gives very comparable results with other three generally acknowledged methods, including the linear extension (LE), window function (WF), and mirror symmetry (MS) based methods. That is, the proposed method can reduce end effects and improve decomposition results of EMD significantly.

Sign in / Sign up

Export Citation Format

Share Document