Detecting Cluster Synchronization in Chaotic Dynamic Networks via Information Theoretic Measures


42nd International Conference on Telecommunications and Signal Processing (TSP), Budapest, Hungary, 1 - 03 July 2019, pp.521-524 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/tsp.2019.8768823
  • City: Budapest
  • Country: Hungary
  • Page Numbers: pp.521-524
  • Keywords: cluster synchronization, information theory, transfer entropy, NEIGHBORS
  • Dokuz Eylül University Affiliated: Yes


Sub-systems in a network of chaotic dynamic systems can form clusters of synchronization. In this study, we investigate the problem of detection of cluster synchronization via information theoretic measures. We have shown that, if the existing information measures in the literature, particularly transfer entropy, is estimated from sequential observations of continuous chaotic systems, it is hard to detect cluster synchronization, directly. On the other hand, if the state space is reconstructed from the observed data in the light of Takens' embedding theorem first, the cluster synchronization can be detected easily.