存在传播延迟的自同步网络最优分散估计

G. Scutari, S. Barbarossa, L. Pescosolido
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引用次数: 13

摘要

本文研究了一种传感器网络方案,该方案的节点是根据微分方程随时间演化的局部耦合振子,其参数依赖于局部估计。该系统能够通过自同步,达到与全局最优最大似然估计一致的网络共识,即使每个传感器仅与附近节点局部耦合。我们的主要贡献是研究传播延迟对系统同步能力和最终估计的影响。我们提供了系统同步的延迟无关条件,并推导了同步状态的封闭表达式。有趣的是,传播延迟的影响只是在最终估计中引入一个偏差,这取决于网络拓扑和延迟的值。通过对这种偏差的分析,建议我们如何设计耦合机制以减轻甚至消除这种偏差
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Optimal Decentralized Estimation Through Self-Synchronizing Networks in the Presence of Propagation Delays
In this paper we focus on a sensor network scheme whose nodes are locally coupled oscillators that evolve in time according to a differential equation, whose parameters depend on the local estimate. The proposed system is capable, by self-synchronization, to reach the network consensus that coincides with the globally optimum maximum likelihood estimate, even though each sensor is only locally coupled with nearby nodes. Our main contribution is to study the effect of propagation delay on both the synchronization capability of the system and the final estimate. We provide delay-independent conditions for the proposed system to synchronize, and we derive closed-form expression of the synchronized state. Interestingly, the effect of propagation delays is simply to introduce a bias on the final estimate, that depends on the network topology and on the values of the delays. The analysis of this bias, suggest us how to design the coupling mechanism in order to alleviate it or even remove it
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