Recurrence plots of experimental data: To embed or not to embed?

被引:161
作者
Iwanski, JS [1 ]
Bradley, E
机构
[1] Univ Colorado, Dept Appl Math, Boulder, CO 80309 USA
[2] Univ Colorado, Dept Comp Sci, Boulder, CO 80309 USA
关键词
D O I
10.1063/1.166372
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A recurrence plot is a visualization tool for analyzing experimental data. These plots often reveal correlations in the data that are not easily detected in the original time series. Existing recurrence plot analysis techniques, which are primarily application oriented and completely quantitative, require that the time-series data first be embedded in a high-dimensional space, where the embedding dimension d(E) is dictated by the dimension d of the data set, with d(E) greater than or equal to 2d + 1. One such set of recurrence plot analysis tools, recurrence quantification analysis, is particularly useful in finding locations in the data where the underlying dynamics change. We have found that for certain low-dimensional systems the same results can be obtained with no embedding. (C) 1998 American Institute of Physics. [S1054-1500(98)00604-1].
引用
收藏
页码:861 / 871
页数:11
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