Chin. Phys. Lett.  2009, Vol. 26 Issue (10): 100502    DOI: 10.1088/0256-307X/26/10/100502
GENERAL |
A Novel Adaptive Predictor for Chaotic Time Series
BU Yun1, WEN Guang-Jun1, ZHOU Xiao-Jia2, ZHANG Qiang3
1School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 6100542College of Automation, University of Electronic Science and Technology of China, Chengdu 6100543School of Sciences, Southwest Petroleum University, Chengdu 610500
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BU Yun, WEN Guang-Jun, ZHOU Xiao-Jia et al  2009 Chin. Phys. Lett. 26 100502
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Abstract Many chaotic time series show non-Gaussian distribution, and non-Gaussianity can be characterized not only by higher-order cumulants but also by negative entropy. Since negative entropy can be accurately approximated by some special non-polynomial functions, which also can form an orthogonal system, these functions are used to construct an adaptive predictor to replace higher-order cumulants. Simulation shows the algorithm performs well for different chaotic systems.
Keywords: 05.45.+b     
Received: 19 February 2009      Published: 27 September 2009
PACS:  05.45.+b  
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https://cpl.iphy.ac.cn/10.1088/0256-307X/26/10/100502       OR      https://cpl.iphy.ac.cn/Y2009/V26/I10/100502
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BU Yun
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