基于奇异熵的混沌时间序列降噪方法

Haibo Yang, Ji-Cong Chen, Shuai Su
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引用次数: 4

摘要

提出了一种基于奇异谱的混沌时间序列降噪方法。一方面,奇异谱对混沌时间序列具有较好的降噪效果。另一方面,如何确定奇异谱的阶数还没有提出。如果选择的阶数过高,则无法完全降低噪声。如果选择的阶数过低,信号的完整性会受到失真。因此,在基于奇异谱的混沌降噪技术中,阶数的选择是非常重要的。本文提出了一种基于奇异熵的新算法。奇异熵的增量随奇异谱阶的变化而敏感。最后,实验结果表明,该方法对于混沌时间序列降噪顺序的确定是非常有效的。
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Noise Reduction for Chaotic Time Series Based on Singular Entropy
The method is proposed for noise reduction of chaotic time series technique based on singularity spectrum. On the one hand, singularity spectrum has a good performance in the noise reduction for chaotic time series. On the other hand, what determine the order of singularity spectrum have not proposing. If the order selected is too high, full reduction of noise is not achieved. If the order selected is too low, the completeness of signal suffers distortion. So the order selected is a very important in chaotic noise reduction technique based on singularity spectrum. A novel arithmetic based on singularity entropy is introduced in this paper. The increment of singularity Entropy is sensitive with change of the order of singularity spectrum. Finally, experimental results show that the method is quite effective for determining noise reduction order in the field of chaotic time series.
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