Cluster stochastic synchronization of complex dynamical networks via fixed-time control scheme. (April 2020)

• Record Type: Journal Article
• Authors: Zhang, Wanli; Li, Chuandong; Li, Hongfei; Yang, Xinsong
• Is Part Of: Neural networks. Volume 124(2020)
• Page Start: 12
• Page End: 19
• Publication Date: 2020-04
• Subjects: Cluster synchronization -- Complex dynamical networks -- Stochastic perturbations -- Quantization -- Fixed-time technique; Neural computers -- Periodicals; Neural networks (Computer science) -- Periodicals; Neural networks (Neurobiology) -- Periodicals; Nervous System -- Periodicals; Ordinateurs neuronaux -- Périodiques; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux neuronaux (Neurobiologie) -- Périodiques; Neural computers; Neural networks (Computer science); Neural networks (Neurobiology); Periodicals; 006.32
• DOI: 10.1016/j.neunet.2019.12.019
• Languages: English
• ISSNs: 0893-6080

Abstract

Abstract: By means of fixed-time (FDT) control technique, cluster stochastic synchronization of complex networks (CNs) is investigated. Quantized controller is designed to realize the synchronization of CNs within a settling time. FDT synchronization criteria are established with the help of Lyapunov functional and comparison system methods. It should be noted that the convergence of synchronization is further improved by comparing with existing FDT synchronization results. Numerical simulations are given to illustrate our results.