Noise Reduction of Chaotic Signals Based on Phase Space Reconstruction and Singular Spectrum Analysis

被引：3

作者：

Chen Y. ^{[1
]}

Liu X. ^{[1
]}

Ren Z. ^{[1
]}

Wu Z. ^{[1
]}

Feng J. ^{[1
]}

机构：

[1] School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640, Guangdong

来源：

Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science) | 2018年 / 46卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Chaotic signal; Noise reduction; Phase space reconstruction; Singular spectrum analysis;

D O I：

10.3969/j.issn.1000-565X.2018.03.009

中图分类号：

学科分类号：

摘要：

To reconstruct chaotic signals from noisy observation data, an adaptive noise reduction method based on phase space reconstruction and singular spectrum analysis (SSA) is proposed.Due to the noise-like nature of chaos, it is difficult to identify the number of the singular values corresponding to the signal components when applying conventional SSA method to chaotic signals.To address this issue, the number of the singular values is estimated by comparing the statistical difference between the chaotic signals and the noise in the phase space.Accordingly, an adaptive noise reduction algorithm is designed.Noise reduction experiments corresponding to both chaotic signals generated by computer and the monthly mean sunspot number series are carried out.The results show that the proposed method can precisely estimate the number of the singular values of the signals, and effectively reconstruct the original chaotic signals.Compared with the conventional chaotic signal denoising methods, the proposed method has advantages in terms of both noise reduction performance and phase portrait restructuring quality. © 2018, Editorial Department, Journal of South China University of Technology. All right reserved.

引用

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页码：58 / 64and91

页数：6433

共 19 条

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