A Bayesian Approach to Sequential Change Detection and Isolation Problems

被引：1
|
作者：
Chen, Jie [1 ,2 ]
Zhang, Wenyi [1 ,2 ]
Poor, H. Vincent [3 ]
机构：
[1] Univ Sci & Technol China, CAS Key Lab Wireless Opt Commun, Hefei 230027, Peoples R China
[2] Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Hefei 230027, Peoples R China
[3] Princeton Univ, Dept Elect Engn, Princeton, NJ 08544 USA
来源：
IEEE TRANSACTIONS ON INFORMATION THEORY | 2021年 / 67卷 / 03期
基金：
美国国家科学基金会; 中国国家自然科学基金;
关键词：
Bayes methods; Delays; Upper bound; Change detection algorithms; Random variables; Stochastic systems; Probability distribution; Asymptotic behavior; average detection delay; Bayesian change detection; change detection and isolation; decision procedures;
D O I：
10.1109/TIT.2020.3042878
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The problem of sequential change detection and isolation under the Bayesian setting is investigated, where the change point is a random variable with a known distribution. A recursive algorithm is proposed, which utilizes the prior distribution of the change point. We show that the proposed decision procedure is guaranteed to control the false alarm probability and the false isolation probability separately under certain regularity conditions, and it is asymptotically optimal with respect to a Bayesian criterion.
引用
收藏
页码：1796 / 1803
页数：8
相关论文
共 50 条
  • [41] An online Bayesian approach to change-point detection for categorical data
    Fan, Yiwei
    Lu, Xiaoling
    KNOWLEDGE-BASED SYSTEMS, 2020, 196
  • [42] Sequential Detection of Multiple Change Points in Networks: A Graphical Model Approach
    Amini, Arash Ali
    XuanLong Nguyen
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2013, 59 (09) : 5824 - 5841
  • [43] A sequential Monte Carlo filtering approach to fault detection and isolation in nonlinear systems
    Kadirkamanathan, V
    Li, P
    Jaward, MH
    Fabri, SG
    PROCEEDINGS OF THE 39TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-5, 2000, : 4341 - 4346
  • [44] A Sequential Bayesian Cumulative Conformance Count Approach to Deterioration Detection in High Yield Processes
    Toubia-Stucky, Gracia
    Liao, Haitao
    Twomey, Janet
    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2012, 28 (02) : 203 - 214
  • [45] Study on the sequential Bayesian approach for a CsI(Tl)-based radioactive material detection system
    Fang, Xinchao
    Wu, Jian
    Yuan, Yonggang
    He, Jingtao
    Qu, Jinhui
    Zeng, Ming
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2022, 1038
  • [46] A Sequential Bayesian Partitioning Approach for Online Steady-State Detection of Multivariate Systems
    Wu, Jianguo
    Xu, Honglun
    Zhang, Chen
    Yuan, Yuan
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2019, 16 (04) : 1882 - 1895
  • [47] Asymptotically optimal Bayesian sequential change detection and identification rules (vol 208, 337, 2013)
    Dayanik, Savas
    Powell, Warren B.
    Yamazaki, Kazutoshi
    ANNALS OF OPERATIONS RESEARCH, 2024, 332 (1-3) : 1275 - 1276
  • [48] Sequential sparsification for change detection
    Ozay, Necmiye
    Sznaier, Mario
    Camps, Octavia I.
    2008 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-12, 2008, : 1014 - 1019
  • [49] Sequential change detection revisited
    Moustakides, George V.
    ANNALS OF STATISTICS, 2008, 36 (02): : 787 - 807
  • [50] Sequential Detection and Isolation of a Correlated Pair
    Chaudhuri, Anamitra
    Fellouris, Georgios
    2020 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2020, : 1141 - 1146
12345