Eigenvalue decomposition as a generalized synchronization cluster analysis
Eigenvalue decomposition as a generalized synchronization cluster analysis
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DOI：
10.1142/s0218127407019251
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发表时间：
2007-10-01
影响因子：
2.2
通讯作者：
Kurths, Jurgen
中科院分区：
文献类型：
--
作者：
Allefeld, Carsten;Mueller, Markus;Kurths, Jurgen
由于最近证明了它作为多变量时间序列中相位形状相关性检测和表征的工具，我们表明特征值分解也可以应用于二元相位同步强度指标矩阵。由此产生的方法是能够识别集群的同步振荡器，并量化他们的强度以及参与程度的振荡器在一个集群。由于对于单个集群的情况，该方法给出的结果与我们之前的方法相似，因此可以将其视为广义同步聚类分析，将其应用领域扩展到更复杂的情况。通过仿真数据验证了该方法的有效性。
Motivated by the recent demonstration of its use as a tool for the detection and characterization of phase-shape correlations in multivariate time series, we show that eigenvalue decomposition can also be applied to a matrix of indices of bivariate phase synchronization strength. The resulting method is able to identify clusters of synchronized oscillators, and to quantify their strength as well as the degree of involvement of an oscillator in a cluster. Since for the case of a single cluster the method gives similar results as our previous approach, it can be seen as a generalized Synchronization Cluster Analysis, extending its field of application to more complex situations. The performance of the method is tested by applying it to simulation data.