Öbek Eşzamanlılığın Nedensellik Entropisi ile Belirlenmesi

Abstract

Kaotik sistemler birbirine durum değişkenleri üzerinden bağlandığında uygun şartlarda öbek eşzamanlılık gerçekleştirebileceği bilinmektedir. Sürekli zamanlı sistemlerden oluşan böyle bir ağda örneklenmiş gözlem vektörleri kullanılarak ağın içindeki öbeklerin belirlenmesi problemi ele alınmıştır. Buna ek olarak; ağ içerisinde bağlantı şiddetinin değişmesi sonucu yeni öbekler oluşursa öbeklerin yeniden belirlenebileceği ön görülmektedir. Öbek eşzamanlılığın belirlenmesi için bilgi kuramı ölçütlerinden biri olan nedensellik entropisi ölçütünün kestirimleri yapılmıştır. Bu ölçüt aynı ya da farklı öbekte olan kaotik sistemleri birbirinden ayrıştırmaktadır. 

Keywords

• Eşzamanlılık,Bilgi kuramı,Nedensellik entropisi,Öbek eşzamanlılık

Detection of Cluster Synchronization via Causation Entropy

Abstract

When chaotic systems are coupled to each other through state variables, the cluster synchronization can occur in the proper circumstances. The problem of detection of cluster synchronization by using observation samples has been investigated in a coupled continuous time chaotic network. If the coupling strengths of this network change, the network can form new clusters. The detection of clusters has been also determined in case of rearranging clusters. In order to detect cluster synchronization,  the causation entropy has been estimated from observation vectors. This measure has been shown to distinguish the systems forming in the network. 

Keywords

• Synchronization,Information theory,Causation entropy,Cluster Synchronization

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