Recurrence plot analysis of irregularly sampled data
Recurrence plot analysis of irregularly sampled data
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DOI：
10.1103/physreve.98.052215
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发表时间：
2018-11
影响因子：
2.4
通讯作者：
Ibrahim Ozken;Deniz Eroglu;S. Breitenbach;N. Marwan;L. Tan;U. Tirnakli;J. Kurths
中科院分区：
文献类型：
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作者：
Ibrahim Ozken;Deniz Eroglu;S. Breitenbach;N. Marwan;L. Tan;U. Tirnakli;J. Kurths
在应用所需的时间序列分析之前，不规则采样时间序列通常需要对数据进行预处理。提出了一种直接适用于不规则采样时间序列的数据点对距离测量方法。为了将递归图分析应用于不规则采样的时间序列，我们使用这种方法来检测原型模型和古气候学中的状态转变。这种方法可能对任何基于距离测量的方法都有用，例如，相关和或李雅普诺夫指数估计。
Irregularly sampled time series usually require data preprocessing before a desired time-series analysis can be applied. We propose an approach for distance measuring of pairs of data points which is directly applicable to irregularly sampled time series. In order to apply recurrence plot analysis to irregularly sampled time series, we use this approach and detect regime transitions in prototypical models and for an application from palaeoclimatatology. This approach might be useful for any method that is based on distance measuring, e.g., correlation sum or Lyapunov exponent estimation.