@inproceedings{20f20fcf75a04661a29e1dbf42671674,
title = "A New Measure for Locally t-Diagnosable Under PMC Model",
abstract = "PMC model is the test-based diagnosis which a vertex performs the diagnosis by testing the neighbor vertices via the edges between them. Hsu and Tan proposed two structures to diagnose a vertex. But these structures don{\textquoteright}t always exist for any vertex. Here, we propose a new testing structure to diagnose a vertex under PMC model to solve the problem above. It can fit more general networks. Let S be a set of faulty edges of the n-dimensional hypercube Qn. Using this structure, we show that every vertex u of Qn is degQn-S(u) -diagnosable if δ(Qn- S) ≥ 2, degQn-S(x)+degQn-S(y)≥5 for every two adjacent vertices x and y in Qn- S, and n≥ 5.",
author = "Meirun Chen and Hsu, {D. Frank} and Lin, {Cheng Kuan}",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 27th International Conference on Computing and Combinatorics, COCOON 2021 ; Conference date: 24-10-2021 Through 26-10-2021",
year = "2021",
doi = "10.1007/978-3-030-89543-3_26",
language = "English",
isbn = "9783030895426",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "306--316",
editor = "Chi-Yeh Chen and Wing-Kai Hon and Ling-Ju Hung and Chia-Wei Lee",
booktitle = "Computing and Combinatorics - 27th International Conference, COCOON 2021, Proceedings",
address = "德國",
}