基于检测系统非线性相关性的相空间重构时间延迟估计
Estimating delay time in phase space reconstruction based on detecting nonlinear correlation of system
A new method to determine delay time is proposed, which is called nonlinear multiple autocorrelation function method. The method uses a high order multiple autocorrelation function, R(τ), to calculate the nonlinear correlation of system and estimates the optimal delay time by finding the first local minimum value of R(τ). The time complexity is low and the dependence on the length of data is not strong. The performance of the algorithm is tested by being applied to five noisy chaotic time series. The time series are generated by four chaotic maps adding different noise level Gauss white noise. The numerical results show that, the method is more appropriate and robust to noise.
混沌时间序列 / 噪声水平 / 相空间重构 / 嵌入维数 / 时间延迟 {{custom_keyword}} /
chaotic time series / noise level / phase space reconstruction / embedding dimension / delay time {{custom_keyword}} /
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