1673-159X

CN 51-1686/N

李显勇,杜亚军,范永全,等. 二进制递归网络的随机多故障条件诊断性综述[J]. 西华大学学报(自然科学版),2021,40(3):31 − 38 . doi: 10.12198/j.issn.1673-159X.3508
引用本文: 李显勇,杜亚军,范永全,等. 二进制递归网络的随机多故障条件诊断性综述[J]. 西华大学学报(自然科学版),2021,40(3):31 − 38 . doi: 10.12198/j.issn.1673-159X.3508
LI Xianyong, DU Yajun, FAN Yongquan, et al. Survey on Random Multi-Fault Conditional Diagnosibility of Binary Recursive Networks[J]. Journal of Xihua University(Natural Science Edition), 2021, 40(3): 31 − 38 . doi: 10.12198/j.issn.1673-159X.3508
Citation: LI Xianyong, DU Yajun, FAN Yongquan, et al. Survey on Random Multi-Fault Conditional Diagnosibility of Binary Recursive Networks[J]. Journal of Xihua University(Natural Science Edition), 2021, 40(3): 31 − 38 . doi: 10.12198/j.issn.1673-159X.3508

二进制递归网络的随机多故障条件诊断性综述

Survey on Random Multi-Fault Conditional Diagnosibility of Binary Recursive Networks

  • 摘要: 二进制递归网络(BR网络)具有结构规则、易于分割等优点,是理论研究和实际应用中颇受欢迎的网络结构。文章在综述互连网络的(强)诊断度、条件诊断度、g-好邻居条件诊断度、g-额外条件诊断度、诊断算法和二进制递归网络研究现状的基础上,针对二进制递归网络的故障结点数大于连通度的随机多故障模式,提出二进制递归网络的随机多故障条件诊断性分析的理论与方法,包括多故障条件诊断度分析、多故障条件诊断策略构建和多故障条件诊断算法设计。

     

    Abstract: Due to the regular in structure and easy division of binary recursive network (BR network), it is a popular network structure in theoretical research and practical application. This paper first surveys the (strong) diagnosability, conditional diagnosability, g-good-neighbor conditional diagnosability, g-extra conditional diagnosability, diagnosis algorithms and binary recursive network. Then on the random multi-fault mode that the binary recursive network's failure nodes are greater than its connectivity, this paper proposes the theory and method of random multi-fault diagnosis analysis for BR network, including multi-fault conditional diagnosis analysis, multi-fault conditional diagnosis strategy construction, and multi-fault conditional diagnosis algorithm design.

     

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