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

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。

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.