Paper
24 October 2006 An improved empirical mode decomposition based on combining extrapolating extrema with mirror extension
Duanhui Duan, Qiusheng Wang
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Abstract
Empirical mode decomposition is a newly developed method used to analyze nonlinear and nonstationary signals. It has been applied to many engineering domains and has represented some unique advantages. However, in the sifting process of empirical mode decomposition, there is an involved end issue during the course of fitting the upper and lower envelops of the signal by cubic spline function. To deal with the problem, an improved empirical mode decomposition is proposed in this paper. It is based on combining extrapolating extrema with mirror extension. The proposed method can solve the problem that the boundaries of the signal will swing widely when the cubic spline interpolation is used to construct the two envelopes of the signal. The capabilities of the proposed method, the method based on mirror extension and the method based on AR model extension algorithm will be compared in the simulation experiments. The experimental results demonstrate that the proposed method can restrain the end effects effectively.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Duanhui Duan and Qiusheng Wang "An improved empirical mode decomposition based on combining extrapolating extrema with mirror extension", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63570X (24 October 2006); https://doi.org/10.1117/12.716909
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Cited by 1 scholarly publication.
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KEYWORDS
Mirrors

Signal processing

Autoregressive models

Surface plasmons

Signal to noise ratio

Fourier transforms

Nonlinear optics

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