| 基于最大Lyapunov指数不变性的混沌时间序列噪声水平估计 |
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| 引用本文： | 姚天亮,刘海峰,许建良,李伟锋. 基于最大Lyapunov指数不变性的混沌时间序列噪声水平估计[J]. 物理学报, 2012, 61(6): 60503-060503 |
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| 作者姓名： | 姚天亮 刘海峰 许建良 李伟锋 |
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| 作者单位： | 华东理工大学 煤气化教育部重点实验室, 上海 200237;华东理工大学 煤气化教育部重点实验室, 上海 200237;华东理工大学 煤气化教育部重点实验室, 上海 200237;华东理工大学 煤气化教育部重点实验室, 上海 200237 |
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| 基金项目： | 国家重点基础研究发展计划(批准号：2010CB227005)、国家自然科学基金(批准号:20906020)和教育部新世纪优秀人才计划(批准号:NCET-08-0775)资助的课题. |
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| 摘 要： | 提出了一种基于最大Lyapunov指数不变性的计算混沌时间序列噪声水平的新方法. 首先分析了噪声对相空间中两点距离的影响, 然后基于最大Lyapunov指数在不同维数的嵌入相空间不变的性质, 建立了估计噪声水平的方法. 仿真计算结果表明, 当噪声水平小于10% 时, 估计值与真实值符合良好. 该方法对噪声分布类型不敏感, 是一种有效的混沌时间序列噪声估计方法.
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| 关 键 词： | 混沌 时间序列 最大Lyapunov指数 噪声 |
| 收稿时间： | 2011-05-14 |
| 修稿时间： | 2011-08-09 |
Noise-level estimation of noisy chaotic time series based on the invariant of the largest Lyapunov exponent |
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| Yao Tian-Liang,Liu Hai-Feng,Xu Jian-Liang and Li Wei-Feng. Noise-level estimation of noisy chaotic time series based on the invariant of the largest Lyapunov exponent[J]. Acta Physica Sinica, 2012, 61(6): 60503-060503 |
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| Authors: | Yao Tian-Liang Liu Hai-Feng Xu Jian-Liang Li Wei-Feng |
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| Affiliation: | Key Laboratory of Coal Gasification, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;Key Laboratory of Coal Gasification, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;Key Laboratory of Coal Gasification, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;Key Laboratory of Coal Gasification, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China |
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| Abstract: | A novel method of estimating the noise level from a noisy chaotic time series based on the invariant of the largest Lyapunov exponent is presented in this paper. The influence of noise on the distance between two points in an embedding phase space is considered, and then based on the invariant of the largest Lyapunov exponent in a different dimensional embedding phase space, the algorithm is proposed to estimate the noise level. Simulation results show that the estimated values of noise level agree well with the true values when the noise level is less than 10%. And this method is not sensitive to the distribution of noise. Therefore, the method is useful for estimating the noise level of noisy chaotic time series. |
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| Keywords: | chaos time series the largest Lyapunov exponent noise |
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