Noise reduction method for chaotic signals based on dual-wavelet and spatial correlation
Noise reduction method for chaotic signals based on dual-wavelet and spatial correlation
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基于双小波和空间相关的混沌信号降噪方法
DOI：
10.1016/j.eswa.2009.01.021
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发表时间：
2009-08
影响因子：
8.5
通讯作者：
Liu, Yunxia
中科院分区：
文献类型：
--
作者：
Han, Min;Liu, Yunxia
本文提出了一种有效的降噪方法来去除混沌信号中的高斯噪声。该方法包括两个主要步骤：小波分解尺度的优选和小波系数的估计，前者由基于双小波的噪声残差比确定，后者结合奇异谱分析和空间相关理论进行分析。分别对Lorenz模型产生的混沌信号和观测到的太阳黑子月序列进行了仿真分析，实验结果表明该方法的性能上级其他方法。
In this paper, an effective noise reduction method is proposed to remove Gaussian noise embedded in chaotic signals. The proposed method has two major steps: an optimal choice of wavelet decomposition scales and an estimation of the wavelet coefficients; the former is determined by the noise residual ratio based on dual-wavelet, whereas the latter is analyzed combining with the singular spectrum analysis and the spatial correlation theory. The chaotic signals generated by Lorenz model as well as the observed monthly series of sunspots are, respectively, applied for simulation analysis, the experimental results show that the performance of the proposed method is superior to that of other methods.
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DOI：
10.2139/ssrn.415361
发表时间：
2003-06
期刊：
Durham Business School Research Paper Series
影响因子：
--
作者：
Antonios Antoniou;Costas E. Vorlow
通讯作者：
Antonios Antoniou;Costas E. Vorlow
影响因子：
2.5
作者：
MALLAT, S;HWANG, WL
通讯作者：
HWANG, WL
影响因子：
9.4
作者：
Fradkov, AL;Evans, RJ
通讯作者：
Evans, RJ
影响因子：
2.6
作者：
D. Smirnov;V. S. Vlaskin;V. Ponomarenko
通讯作者：
D. Smirnov;V. S. Vlaskin;V. Ponomarenko
影响因子：
2.4
作者：
Zidong Wang;J. Lam;Xiaohui Liu
通讯作者：
Zidong Wang;J. Lam;Xiaohui Liu