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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2023 Vol.24 No.9 P.1349-1356
Impact of distance between two hubs on the network coherence of tree networks
Abstract: We study the impact of the distance between two hubs on network coherence defined by Laplacian eigenvalues. Network coherence is a measure of the extent of consensus in a linear system with additive noise. To obtain an exact determination of coherence based on the distance, we choose a family of tree networks with two hubs controlled by two parameters. Using the tree’s regular structure, we obtain analytical expressions of the coherences with regard to network parameters and the network size. We then demonstrate that a shorter distance and a larger difference in the degrees of the two hubs lead to a higher coherence. With the same network size and distance, the best coherence occurs in the tree with the largest difference in the hub’s degrees. Finally, we establish a correlation between network coherence and average path length and find that they behave linearly.
Key words: Consensus; Coherence; Distance; Average path length
杭州电子科技大学理学院,中国杭州市,310018
摘要:本文研究了两个中心节点之间的距离对网络一致性的影响。网络一致性由拉普拉斯特征值所量化,可用来衡量线性系统对外部噪声的一致性程度。为获得网络一致性关于距离的精确表达式,选取一类由网络参数控制的具有两个中心节点的树状网络。利用其规则的拓扑结构,得到一致性关于网络参数和网络规模的解析表达式。证明两个中心节点距离越短,度的差异性越大,网络一致性越好。在相同网络规模和距离下,最大的中心节点度差异会导致最优的一致性。最后,建立了网络一致性与平均路径长度之间的联系,发现它们呈线性关系。
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DOI:
10.1631/FITEE.2200400
CLC number:
N941
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On-line Access:
2023-06-21
Received:
2022-09-18
Revision Accepted:
2023-09-21
Crosschecked:
2023-03-31