Cluster Synchronization in Hybrid Coupled Discrete-Time Delayed Complex Networkst

This paper studies the exponential cluster synchronization in arrays of coupled discrete-time dynamical networks with time-varying delay, in which the hybrid coupling is involved. Through choosing two improved Lyapunov- Krasovskii functionals, some delay-dependent sufficient conditions are presented...

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Bibliographic Details
Published in理论物理通讯：英文版 Vol. 58; no. 11; pp. 686 - 696
Main Author LI Tao WANG Ting YANG Xin FEI Shu-Min
Format Journal Article
LanguageEnglish
Published 2012
Subjects
Lyapunov-Krasovskii泛函
Matlab
动力耦合
动态网络
时变时滞
混合
离散时间
群同步
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Summary:This paper studies the exponential cluster synchronization in arrays of coupled discrete-time dynamical networks with time-varying delay, in which the hybrid coupling is involved. Through choosing two improved Lyapunov- Krasovskii functionals, some delay-dependent sufficient conditions are presented based on reciprocal convex technique and Kronecker product. These criteria are presented in terms of LMIs and their feasibility can be easily checked by resorting to Matlab LMI Toolbox. Moreover, the addressed system can include some famous network models as its special cases and the effective techniques are used, which can extend some earlier reported results. Finally, the effectiveness of the proposed methods can be further illustrated with the help of two numerical examples.
Bibliography:11-2592/O3
This paper studies the exponential cluster synchronization in arrays of coupled discrete-time dynamical networks with time-varying delay, in which the hybrid coupling is involved. Through choosing two improved Lyapunov- Krasovskii functionals, some delay-dependent sufficient conditions are presented based on reciprocal convex technique and Kronecker product. These criteria are presented in terms of LMIs and their feasibility can be easily checked by resorting to Matlab LMI Toolbox. Moreover, the addressed system can include some famous network models as its special cases and the effective techniques are used, which can extend some earlier reported results. Finally, the effectiveness of the proposed methods can be further illustrated with the help of two numerical examples.
discrete-time, delayed neural networks （DNNs）, exponential cluster synchronization, Kroneckerproduct, LMI approach
ISSN:0253-6102