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二进制递归网络的随机多故障条件诊断性综述
引用本文:李显勇,杜亚军,范永全,陈晓亮. 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
作者姓名:李显勇  杜亚军  范永全  陈晓亮
作者单位:西华大学计算机与软件工程学院,四川 成都 610039
基金项目:国家自然科学基金项目(61802316,61872298,61532009,61472329,61902324,61602389);教育部春晖计划科研合作项目(Z2015109,Z2012030,Z2015100);四川省教育厅基金项目(15ZA0130,16ZA0157);四川省科技厅项目(2017HH0083,2018GZ0096);西华大学青年学者后备人才项目;西华大学自然科学重点基金项目(z1422615);省部级学科平台开放课题(szjj2015-057,szjj2016-023);西华大学计算机与软件工程学院杰出青年学者培育计划项目
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...

关 键 词:互连网络  二进制递归网络  故障诊断  多故障模式  条件诊断度  诊断策略
收稿时间:2020-05-02

Survey on Random Multi-Fault Conditional Diagnosibility of Binary Recursive Networks
LI Xianyong,DU Yajun,FAN Yongquan,CHEN Xiaoliang. 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
Authors:LI Xianyong  DU Yajun  FAN Yongquan  CHEN Xiaoliang
Affiliation:School of Computer and Software Engineering, Xihua University, Chengdu 610039 China
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.
Keywords:
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