Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

作     者：王文波 张晓东 常毓禅 汪祥莉 王钊 陈希 郑雷 

作者机构：College of ScienceWuhan University of Science and TechnologyWuhan 430065China State Key Laboratory of Satellite Ocean Environment DynamicsSecond Institute of OceanographyState Oceanic AdministrationHangzhou 310012China School of FinanceRenmin University of ChinaBeijing 100872China School of Computer Science and TechnologyWuhan University of TechnologyWuhan 430063China College of Information Science and EngineeringWuhan University of Science and TechnologyWuhan 430081China Wuhan NARI Limited Liability Company of Sate Grid Electric Power Research InstituteWuhan 430074China 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2016年第25卷第1期

页      面：400-406页

核心收录：

学科分类：11[军事学] 0810[工学-信息与通信工程] 1105[军事学-军队指挥学] 08[工学] 081002[工学-信号与信息处理] 110503[军事学-军事通信学] 

基　　金：supported by the National Science and Technology,China(Grant No.2012BAJ15B04) the National Natural Science Foundation of China(Grant Nos.41071270 and 61473213) the Natural Science Foundation of Hubei Province,China(Grant No.2015CFB424) the State Key Laboratory Foundation of Satellite Ocean Environment Dynamics,China(Grant No.SOED1405) the Hubei Provincial Key Laboratory Foundation of Metallurgical Industry Process System Science,China(Grant No.Z201303) the Hubei Key Laboratory Foundation of Transportation Internet of Things,Wuhan University of Technology,China(Grant No.2015III015-B02) 

主　　题：independent component analysis empirical mode decomposition chaotic signal denoising 

摘      要：In this paper, a new method to reduce noises within chaotic signals based on ICA （independent component analysis） and EMD （empirical mode decomposition） is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the indepen- dent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions （IMFs） of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor.