147,157 research outputs found

    A new framework for consensus for discrete-time directed networks of multi-agents with distributed delays

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    Copyright @ 2012 Taylor & FrancisIn this article, the distributed consensus problem is considered for discrete-time delayed networks of dynamic agents with fixed topologies, where the networks under investigation are directed and the time-delays involved are distributed time delays including a single or multiple time delay(s) as special cases. By using the invariance principle of delay difference systems, a new unified framework is established to deal with the consensus for the discrete-time delayed multi-agent system. It is shown that the addressed discrete-time network with arbitrary distributed time delays reaches consensus provided that it is strongly connected. A numerical example is presented to illustrate the proposed methods.This work was supported in part by City University of Hong Kong under Grant 7008114, the Royal Society of the UK, the National Natural Science Foundation of China under Grants 60774073 and 61074129, and the Natural Science Foundation of Jiangsu Province of China under Grant BK2010313

    Random consensus protocol in large-scale networks

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    One of the main performance issues for consensus protocols is the convergence speed. In this paper, we focus on the convergence behavior of discrete-time consensus protocols over large-scale sensor networks with uniformly random deployment, which are modelled as Poisson random graphs. Instead of using the random rewiring procedure, we introduce a deterministic principle to locate certain “chosen nodes” in the network and add “virtual” shortcuts among them so that the number of iterations to achieve average consensus drops dramatically. Simulation results are presented to verify the efficiency of this approach. Moreover, a random consensus protocol is proposed, in which virtual shortcuts are implemented by random routes

    The Status of Health Information Delivery in the United States: The Role of Libraries in the Complex Health Care Environment

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