Denoising of chaotic signals based on ensemble empirical mode decomposition and interval thresholding

被引：0

作者：

Wang, Mengjiao ^{[1
,2
]}

Feng, Jiuchao ^{[1
]}

Wu, Zhongtang ^{[1
]}

Wang, Qian ^{[1
]}

机构：

[1] School of Electronic and Information Engineering, South China University of Technology, Guangzhou

[2] Department of Information Science and Engineering, Hunan Institute of Humanities, Science and Technology, Loudi

来源：

Journal of Computational Information Systems | 2015年 / 11卷 / 08期

基金：

中国国家自然科学基金;

关键词：

Chaotic signal denoising; Ensemble empirical mode decomposition; Interval thresholding; Wavelet thresholding;

D O I：

10.12733/jcis14223

中图分类号：

学科分类号：

摘要：

In this paper, a new approach to denoise chaotic signals based on ensemble empirical mode decomposition and interval thresholding (EEMD-IT) is proposed. In our scheme, the EEMD technique is first used to decompose the noisy chaotic signal into the so-called intrinsic mode functions (IMFs). And a novel criterion is proposed to determine the IMFs which need to be smoothed. The interval thresholding technique is then used in the decomposition modes. In the experiments, we compare the proposed method with four existing major methods: the wavelet thresholding, the signal-filtering approach based on empirical mode decomposition (EMD-based), the nonlinear adaptive denoising algorithm and the clear iterative EMD interval thresholding approach (EMD-CIIT). The experimental results show that the proposed method performs better than the first three existing methods. And it has a close performance with EMD-CIIT on denoising. However, unlike EMD-CIIT, the proposed method does not need to use the wavelet thresholding to preprocess the first IMF. So it has a better adaptive filtering performance than EMD-CIIT. ©, 2015, Binary Information Press. All right reserved.

引用

页码：2953 / 2962

页数：9

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