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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50515

Authors: Chu-Kuan Lin
Wei-Po Huang
Grzegorz Różyński
Jaw-Guei Lin
Contributors: 國立臺灣海洋大學:河海工程學系
Keywords: EEMD
Noise-Assisted data analysis method
Date: 2016-10
Issue Date: 2018-10-13T08:12:53Z
Publisher: Journal of Marine Science and Technology
Abstract: Abstract: An adjustment about the added white noise in Ensemble
Empirical Mode Decomposition (EEMD) of Wu and Huang
(2008) was presented in this paper. The EEMD establishes an
ensemble by adding time series of finite but not infinitesimal
amplitude white noise into a time series of the signal to solve
the mode-mixing problem occurred in the conventional EMD
method. The adding ensembles of noise are supposed to be
exhausted from all possible solutions from the sifting process.
However, in the Matlab script of the theory, it was found that
the added noise could not be averaged out through the whole
process. The residue added noise thus causes some extra signals
exist in the sifting results, even the number of trials of the
ensemble was up to 5000. In the adjusted method, the added
noises were randomly selected without repetition from a noise
set which satisfies the normal distribution at each sampled node.
With this approach, the added noises can be entirely averaged
out without any residue at each node and on the entire time
series. The experiments show that number of trials can be reduced
to 50 sets. It not only avoid the time consuming problem
but also retains the benefit of EEMD.
Relation: 25(1) pp.108-118
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50515
Appears in Collections:[河海工程學系] 期刊論文

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