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An improved empirical mode decomposition method using second generation wavelets interpolation.

Authors :
Wang, Jianlin
Wei, Qingxuan
Zhao, Liqiang
Yu, Tao
Han, Rui
Source :
Digital Signal Processing. Aug2018, Vol. 79, p164-174. 11p.
Publication Year :
2018

Abstract

Empirical mode decomposition (EMD) may generate undesirable intrinsic mode functions (IMFs) under low sampling rate, which can significantly affect the results of decomposition. In this paper, an improved EMD method using second generation wavelets interpolation is presented which can eliminate undesirable IMFs and reduce the scale mixing effectively under low sampling rate. Firstly, the original signal under low sampling rate is reconstructed by inverse process of second generation wavelets lifting algorithm. Secondly, the location algorithm of extrema using second generation wavelets is given to obtain the accurate position of extrema. Finally, five examples are demonstrated to justify the effectiveness. Numerical simulation and experimental results are attained to show the effectiveness of the proposed method in eliminating undesirable IMFs and reducing the scale mixing, thereby making the proposed improved EMD a promising method for improving the performance of EMD under low sampling rate. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10512004
Volume :
79
Database :
Academic Search Index
Journal :
Digital Signal Processing
Publication Type :
Periodical
Accession number :
129975577
Full Text :
https://doi.org/10.1016/j.dsp.2018.05.009