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中国物理学会期刊

连续动力系统时间序列的非线性检验

CSTR: 32037.14.aps.54.1059

Detecting the nonlinearity for time series sampled from continuous dynamic systems

CSTR: 32037.14.aps.54.1059
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  • 用相位随机化的替代数据方法,研究了连续混沌动力系统时间序列的非线性检验判定.研究发现,在不同的采样情况下,混沌时间序列的非线性特性检验有所差异,尤其对于过采样时间序列,往往会出现虚假的判断结果.针对过采样时间序列,最好采用能够反映非线性特征的参数,作为检验统计量进行检验判断.

     

    This paper studies the detection of the nonlinearity of time series sampled from continuous dynamics systems by using the surrogate data method. The results show that under the different sampling conditions, the detection finds different nonlinearity of chaotic time series. Especially for the oversampling time series, there can often be some illusive results. For this, we suggest that it is best to apply nonlinear values as testing statistics for detecting nonlinearity of oversampling time series.

     

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