4.6 Article

Further Results for Edge Convergence of Directed Signed Networks

期刊

IEEE TRANSACTIONS ON CYBERNETICS
卷 51, 期 12, 页码 5659-5670

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2019.2933478

关键词

Convergence; Laplace equations; Network topology; Decentralized control; Topology; Cybernetics; Trajectory; Directed signed network; edge convergence; node convergence; r-structural balance; structure balance

资金

  1. National Natural Science Foundation of China [61873013, 61922007, 61573034, 61520106010]
  2. Fundamental Research Funds for the Central Universities [YWF-19-BJ-J-42, YWF-18-BJ-Y-25]

向作者/读者索取更多资源

This article explores the edge convergence problems in directed signed networks, discussing the convergence behavior under different structural properties and providing simulation examples to validate the established results. It addresses the question of how edge states converge in the absence of strong connectivity, with a focus on spanning tree and various structural balance conditions.
The edge convergence problems have been explored for directed signed networks recently in 2019 by Du, Ma, and Meng, of which the analysis results, however, depend heavily on the strong connectivity of the network topologies. The question asked in this article is: whether and how can the edge convergence be achieved when the strong connectivity is not satisfied? The answer for the case of spanning tree is given. It is shown that if a signed network is either structurally balanced or r-structurally unbalanced, then the edge state can be ensured to converge to a constant vector. In contrast, if a signed network is both structurally unbalanced and r-structurally balanced, then its edge state does not converge to a constant vector any longer, but to a time-varying vector trajectory with a constant speed. Further, the dynamic behavior results of edges can be derived to address the node convergence problems of signed networks. The simulation examples are provided to illustrate the validity of the established edge convergence results.

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