Application of Chaos Game Representation to nonlinear time series analysis
Application of Chaos Game Representation to nonlinear time series analysis
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DOI：
10.1142/s0218348x06003064
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发表时间：
2006-03-01
影响因子：
4.7
通讯作者：
Suzuki, M
中科院分区：
文献类型：
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作者：
Suzuki, T;Ikeguchi, T;Suzuki, M
迭代函数系统通常用于研究分形结构。该方法也称为混沌博弈表示(CGR)，用于直观地表示DNA序列的特征结构。在本文中，我们提出了一种绘制 COB 的原始方法。轻松确认时间序列的时间评估的属性。如果我们不小心将 CGR 应用于实时序列，我们还表明了时间序列的虚假特征结构的存在。我们发现，虚假识别的根源来自于时间序列的频率直方图的不均匀性，这通常是分析实时序列的情况。我们还展示了如何通过应用替代数据的方法并引入时间序列的条件概率来避免这种虚假识别。
Iterative function systems are often used for investigating fractal structures. The method is also referred as Chaos Game Representation (CGR), and is applied for representing characteristic structures of DNA sequences visually. In this paper, we proposed an original way of plotting COB. to easily confirm the property of the temporal evaluation of a time series. We also showed existence of spurious characteristic structures of time series, if we carelessly applied the CGR to real time series. We revealed that the source of spurious identification came from non-uniformity of the frequency histograms of the time series, which is often the case of analyzing real time series. We also showed how to avoid such spurious identification by applying the method of surrogate data and introducing conditional probabilities of the time series.