重新排列树以实现鲁棒一致性
Rearranging trees for robust consensus
AI总结：
本文利用与通信图相关的H2范数刻画一致性对噪声的鲁棒性，通过分析局部拓扑变化的影响，为无向树和有向树建立基于H2范数的偏序，并提出一种分散式重排树以提升鲁棒性的方法。
摘要：
在本文中，我们利用与通信图相关的H2范数来刻画一致性对噪声的鲁棒性。特别地，我们将注意力限制在树上，并通过系统关注局部拓扑变化的影响，根据H2范数推导出无向树的偏序。我们的无向树方法为有向树的排序提供了一种构造性方法。此外，我们的方法提出了一种分散式的方式，通过重新排列树来改善其鲁棒性。
英文摘要：
In this paper, we use the H2 norm associated with a communication graph to characterize the robustness of consensus to noise. In particular, we restrict our attention to trees and by systematic attention to the effect of local changes in topology, we derive a partial ordering for undirected trees according to the H2 norm. Our approach for undirected trees provides a constructive method for deriving an ordering for directed trees. Further, our approach suggests a decentralized manner in which trees can be rearranged in order to improve their robustness.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
