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Degree distributions and motif profiles of limited penetrable horizontal visibility graphs

机译:有限可渗透水平可见性图表的学位分布和图案配置文件

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The algorithm of limited penetrable horizontal visibility graphs (LPHVGs) including the limited penetrable horizontal visibility graph [LPHVG(rho)], the directed limited penetrable horizontal visibility graph [DLPHVG(rho)] and the image limited penetrable horizontal visibility graph [ILPHVG(n)(rho))] are used to map time series (or matrices) on graphs and are powerful tools for analyzing time series. We derive the degree distributions of LPHVGs using an iterative LPHVGs construction process. We propose a more intuitive method of reproducing the construction process of limited penetrable horizontal visibility graphs that is simple to calculate. We find that the results confirm the analytical results from previous methods. We then introduce the concept of sequential LPHVG(rho) motifs and present a theoretical way of computing the exact motif profiles associated with unrelated random series. We perform several numerical simulations to further check the accuracy of our theoretical results. Finally we use the analytical results of LPHVG(rho) motif profiles to distinguish among random, periodic, and chaotic signals and find that the frequency of the type-I motif captures sufficient information to easily distinguish among different processes. (C) 2018 Elsevier B.V. All rights reserved.
机译:限量可渗透水平可见性图(LPHVG)的算法(LPHVG),包括有限的可渗透水平可见性图[LPHVG(RHO)],指向有限的可渗透水平可见性图[DLPHVG(RHO)]和图像有限的可渗透水平可见性图[ILPHVG(n )(RHO))]用于在图中映射时间序列(或矩阵),是用于分析时间序列的强大工具。我们使用迭代LPHVGS构造过程导出LPHVG的程度分布。我们提出了一种更直观的方法,可以再现有限可渗透水平可见性图形的结构过程,这是简单的计算。我们发现结果证实了先前方法的分析结果。然后,我们介绍了顺序LPHVG(RHO)图案的概念,并呈现了计算与无关随机系列相关的精确主题配置文件的理论方式。我们执行几种数值模拟,以进一步检查我们理论结果的准确性。最后,我们使用LPHVG(RHO)主题配置文件的分析结果来区分随机,周期性和混沌信号之间,并发现I型图案的频率捕获足够的信息以容易地区分不同的过程。 (c)2018年elestvier b.v.保留所有权利。

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