Detectability vverification of probabilistic Boolean networks

被引:18
|
作者
Han, Xiao-Guang [1 ]
Yang, Wen-Dong [1 ]
Chen, Xiao-Yan [1 ]
Li, Zhi-Wu [2 ,3 ]
Chen, Zeng-Qiang [4 ]
机构
[1] Tianjin Univ Sci & Technol, Coll Elect Informat & Automat, Tianjin 300222, Peoples R China
[2] Macau Univ Sci & Technol, Inst Syst Engn, Taipa 519020, Macao, Peoples R China
[3] Xidian Univ, Sch Electromech Engn, Xian 710071, Peoples R China
[4] Nankai Univ, Coll Artificial Intelligence, Tianjin 300350, Peoples R China
基金
中国国家自然科学基金;
关键词
Probabilistic Boolean networks; Periodic detectability; k-Detectability; d-Detectability; Semi-tensor product of matrices; OBSERVABILITY; STABILITY; STABILIZATION;
D O I
10.1016/j.ins.2020.10.019
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We in this paper study the current-state estimation problem of probabilistic Boolean networks with output observations. First, we propose the concepts of three fundamental categories of detectability in the context of PBNs based on the different purposes, which are periodic detectability, (periodic) k-detectability, and (periodic) d-detectability. Second, utilizing the semi-tensor product technique, we create a uniform methodology for the verification of all the aforementioned categories of detectability. Accordingly, several necessary and sufficient verification criteria are derived. All results obtained in this paper are numerically tractable since they avoid the graph-based symbolic manipulations. Finally, several examples modeled by the same PBN are provided to instantiate the correctness and effeteness of the obtained results. (c) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页码:313 / 327
页数:15
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