Abstract
In this paper, a new method for reducing noise within chaotic signal based on ICA (Independent Component Analysis) and EMD (Empirical Mode Decomposition) is proposed. The basic idea is decomposing chaotic signal and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Then, it makes the independent component analysis on the input vectors, which means a self adapting denoising is carried out for the intrinsic mode functions (IMFs) of chaotic signal. At last, all the IMFs composed the new denoised chaotic signal. An experiment on Lorenz chaotic signal which is composed as different Gaussian noises and monthly observed chaotic sequence on sunspots was put into practice. The result proved the method proposed by this paper is effective in denoising of chaotic signal. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor.
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Li, X., Wang, W. (2013). Studying on Denoising of Chaotic Signal Using ICA and EMD. In: Bian, F., Xie, Y., Cui, X., Zeng, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. Communications in Computer and Information Science, vol 398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45025-9_55
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DOI: https://doi.org/10.1007/978-3-642-45025-9_55
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