Title
An improved bidimensional empirical mode decomposition: A mean approach for fast decomposition
Abstract
In this paper, a mean approach is proposed to accelerate bidimensional empirical mode decomposition (BEMD). In the envelope generation process, the proposed method uses a modified mean filter to approximate the interpolated envelope of the conventional BEMD, and utilizes a convolution algorithm based on singular value decomposition (SVD) to further reduce the computation time. Order statistics filter width determination, originally used in fast and adaptive bidimensional empirical mode decomposition (FABEMD), is applied to adaptively formulate an envelope. Considering the computation efficiency, the proposed method improves the algorithm for calculating distances among extrema by using Delaunay triangulation (DT). The experimental results show that the mean approach can produce intrinsic mode functions faster than FABEMD, while retaining acceptable quality.
Year
DOI
Venue
2014
10.1016/j.sigpro.2013.11.034
Signal Processing
Keywords
Field
DocType
modified mean filter,interpolated envelope,adaptive bidimensional empirical mode,singular value decomposition,intrinsic mode function,mean approach,improved bidimensional empirical mode,computation efficiency,envelope generation process,bidimensional empirical mode decomposition,fast decomposition,empirical mode decomposition,convolution,delaunay triangulation
Singular value decomposition,Mathematical optimization,Median filter,Convolution,Interpolation,Maxima and minima,Mathematics,Hilbert–Huang transform,Computation,Delaunay triangulation
Journal
Volume
ISSN
Citations 
98,
0165-1684
3
PageRank 
References 
Authors
0.48
13
5
Name
Order
Citations
PageRank
Chin-Yu Chen1345.22
Shu-mei Guo231028.94
Wei-Sheng Chang330.81
Jason Hong46706518.75
Kuo-Sheng Cheng528027.81