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摘要


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.

被引用紀錄


吳峰賓(2010)。考慮路面粗糙度與車輛非線性勁度於橋頻間接量測法之模擬分析〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2010.01705
Su, C. W. (2007). 以希爾伯-黃轉換為基礎的去噪音方法以及從腦電儀資料辨識電流源的應用 [master's thesis, National Central University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0031-0207200917350836

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