School of Mathematical Science, Nanjing Normal University, Nanjing 210042, Jiangsu, China.
Department of Mathematics, Nanjing Normal University Taizhou College, Taizhou 225300, Jiangsu, China.
Phys Rev E. 2018 May;97(5-1):052117. doi: 10.1103/PhysRevE.97.052117.
The limited penetrable horizontal visibility graph algorithm was recently introduced to map time series in complex networks. In this work, we extend this algorithm to create a directed-limited penetrable horizontal visibility graph and an image-limited penetrable horizontal visibility graph. We define two algorithms and provide theoretical results on the topological properties of these graphs associated with different types of real-value series. We perform several numerical simulations to check the accuracy of our theoretical results. Finally, we present an application of the directed-limited penetrable horizontal visibility graph to measure real-value time series irreversibility and an application of the image-limited penetrable horizontal visibility graph that discriminates noise from chaos. We also propose a method to measure the systematic risk using the image-limited penetrable horizontal visibility graph, and the empirical results show the effectiveness of our proposed algorithms.
最近引入了有限穿透水平可见度图算法来绘制复杂网络中的时间序列。在这项工作中,我们将该算法扩展到创建有向有限穿透水平可见度图和图像有限穿透水平可见度图。我们定义了两种算法,并提供了与不同类型实值序列相关的这些图的拓扑性质的理论结果。我们进行了几次数值模拟来检查我们理论结果的准确性。最后,我们提出了一种使用有向有限穿透水平可见度图来测量实值时间序列不可逆性的应用,以及一种使用图像有限穿透水平可见度图来区分噪声和混沌的应用。我们还提出了一种使用图像有限穿透水平可见度图来衡量系统性风险的方法,实证结果表明了我们提出的算法的有效性。