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An innovated evolving network representation model to characterize weighted, complex, scale-free networks is proposed. A new node or a community is added to network in the process of evolution while emergences of new links occur according to the ‘Triad Formation’ possessing symmetry and the random selection mechanism. A weighted scale-free network with high-value clustering coefficient can be obtained...
This paper is concerned with the coordinated tracking of linear multi-agent systems with a dynamic leader. The input of the leader is time-varying and cannot be obtained by any follower agents. Distributed iterative learning controllers are developed based on the relative state information of neighboring agents. Lyapunov-Krasovskii functionals are used to show the stability properties of the closed-loop...
The asymptotic synchronization problem of a class of uncertain and delayed chaotic systems is addressed with adaptive compensation designs in this paper. General uncertainties on systems and time-delays in the coupling network are eliminated by the adaptive control scheme, as well as its circuit realization are proposed. Then, an approach that is based on application of Lyapunov stability theory for...
we introduce a evolving model that characterizes the weighted scale-free networks with high clustering coefficient by adjusting a parameter. The average clustering coefficient exhibits power-law decay as a function of degree of node. Triad Formation can distinctly enhance the clustering coefficient of networks. The effect of the evolution mechanism on synchronizability is analyzed. The simulation...
This paper deals with the robust synchronization problem of a class of complex networks with nonlinearly coupled networks. A sliding mode control strategy is proposed to guarantee the compensation of the nonlinear couplings by means of adaptive adjustment of unknown controller parameters. It is shown that, through Lyapunov stability theory, the proposed sliding mode controllers are successful in ensuring...
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