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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Pinning Distributed Synchronization of Stochastic Dynamical Networks: A Mixed Optimization Approach
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Pinning Distributed Synchronization of Stochastic Dynamical Networks: A Mixed Optimization Approach

机译：固定随机动态网络的分布式同步：混合优化方法

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摘要

This paper is concerned with the problem of pinning synchronization of nonlinear dynamical networks with multiple stochastic disturbances. Two kinds of pinning schemes are considered: 1) pinned nodes are fixed along the time evolution and 2) pinned nodes are switched from time to time according to a set of Bernoulli stochastic variables. Using Lyapunov function methods and stochastic analysis techniques, several easily verifiable criteria are derived for the problem of pinning distributed synchronization. For the case of fixed pinned nodes, a novel mixed optimization method is developed to select the pinned nodes and find feasible solutions, which is composed of a traditional convex optimization method and a constraint optimization evolutionary algorithm. For the case of switching pinning scheme, upper bounds of the convergence rate and the mean control gain are obtained theoretically. Simulation examples are provided to show the advantages of our proposed optimization method over previous ones and verify the effectiveness of the obtained results.
机译：本文涉及具有多个随机扰动的非线性动力网络的销钉同步问题。考虑两种钉扎方案：1）钉扎节点在时间演变过程中是固定的； 2）钉扎节点根据一组伯努利随机变量不时切换。使用Lyapunov函数方法和随机分析技术，可以得出一些易于验证的准则来解决固定分布式同步的问题。对于固定固定节点的情况，提出了一种新的混合优化方法来选择固定节点并找到可行的解决方案，该方法由传统的凸优化方法和约束优化演化算法组成。对于切换固定方案，理论上可以得出收敛速度和平均控制增益的上限。仿真算例表明了所提优化方法相对于现有方法的优越性，并验证了所得结果的有效性。

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