Asymptotically Optimal Quickest Change Detection in Distributed Sensor Systems

REFERENCES

• Baron , M. and Tartakovsky , A. G. ( 2006 ). Asymptotic Bayesian Change-Point Detection Theory for General Continuous-Time Models , Sequential Analysis 25 : 257 – 296 .
   Google Scholar
• Basseville , M. and Nikiforov , I. V. ( 1993 ). Detection of Abrupt Changes: Theory and Applications , Englewood Cliffs : Prentice Hall .
   Google Scholar
• Dragalin , V. P. , Tartakovsky , A. G. , and Veeravalli , V. V. ( 1999 ). Multihypothesis Sequential Probability Ratio Tests, Part I: Asymptotic Optimality , IEEE Transactions on Information Theory 45 : 2448 – 2461 .
   Web of Science ®Google Scholar
• Dragalin , V. P. , Tartakovsky , A. G. , and Veeravalli , V. V. ( 2000 ). Multihypothesis Sequential Probability Ratio Tests, Part 2: Accurate Asymptotic Expansions for the Expected Sample Size , IEEE Transactions on Information Theory 46 : 1366 – 1383 .
   Web of Science ®Google Scholar
• Gordon , L. and Pollak , M. ( 1994 ). An Efficient Nonparametric Detection Scheme for Detecting a Change in Distribution , Annals of Statistics 22 : 763 – 804 .
   Web of Science ®Google Scholar
• Kent , S. ( 2000 ). On the Trial of Intrusions into Information Systems , IEEE Spectrum 37 ( 12 ): 52 – 56 .
   Google Scholar
• Lai , T. L. ( 1995 ). Sequential Changepoint Detection in Quality Control and Dynamical Systems , Journal of Royal Statistal Society, Series B 57 : 613 – 658 .
   Google Scholar
• Lai , T. ( 1998 ). Information Bounds and Quick Detection of Parameter Changes in Stochastic Systems , IEEE Transactions on Information Theory 44 : 2917 – 2929 .
   Web of Science ®Google Scholar
• Lorden , G. ( 1971 ). Procedures for Reacting to a Change in Distribution , Annals of Mathematical Statistics 42 : 1897 – 1908 .
   Google Scholar
• Mei , Y. ( 2005 ). Information Bounds and Quickest Change Detection in Decentralized Decision Systems , IEEE Transactions on Information Theory 51 : 2669 – 2681 .
   Web of Science ®Google Scholar
• Moustakides , G. V. ( 1986 ). Optimal Stopping Times for Detecting Changes in Distributions , Annals of Statistics 14 : 1379 – 1387 .
   Web of Science ®Google Scholar
• Moustakides , G. V. ( 2006 ). Decentralized CUSUM Change Detection, Proceedings of the 9th International Conference on Information Fusion (Fusion 2006) , Florence , Italy , July 2006, CD Rom ISBN 0-9721844-6-5 .
   Google Scholar
• Moustakides , G. V. ( 2008 ). Sequential Change Detection Revisited , Annals of Statistics 36 : 787 – 807 .
   Web of Science ®Google Scholar
• Page , E. S. ( 1954 ). Continuous Inspection Schemes , Biometrika 41 : 100 – 115 .
   Web of Science ®Google Scholar
• Pollak , M. ( 1985 ). Optimal Detection of a Change in Distribution , Annals of Satistics 13 : 206 – 227 .
   Web of Science ®Google Scholar
• Pollak , M. ( 1987 ). Average Run Lengths of an Optimal Method of Detecting a Change in Distribution , Annals of Statistics 15 : 749 – 779 .
   Web of Science ®Google Scholar
• Pollak , M. ( 2007 ). Nonparametric Detection of a Change, Proceedings of the 56th Session of the International Statistical Institute (ISI) 22–29 August 2007 , Lisbon , Portugal .
   Google Scholar
• Pollak , M. and Tartakovsky , A. G. ( 2008a ). Asymptotic Exponentiality of the Distribution of First Exit Times for a Class of Markov Processes with Applications to Quickest Change Detection, Theory of Probability and Its Applications, in press .
   Google Scholar
• Pollak , M. and Tartakovsky , A. G. ( 2008b ). Optimality of the Shiryaev–Roberts Procedure , Statistica Sinica , in press .
   Google Scholar
• Siegmund , D. ( 1985 ). Sequential Analysis: Tests and Confidence Intervals , New York : Springer-Verlag .
   Google Scholar
• Shiryaev , A. N. ( 1961 ). The Detection of Spontaneous Effects , Soviet Mathematics—Doklady 2 : 740 – 743 .
   Google Scholar
• Shiryaev , A. N. (1963). On Optimum Methods in Quickest Detection Problems, Theory of Probability and Its Applications 8: 22–46.
   Google Scholar
• Shiryaev , A. N. ( 1978 ). Optimal Stopping Rules , New York : Springer-Verlag .
   Google Scholar
• Tartakovsky , A. G. ( 1991 ). Sequential Methods in the Theory of Information Systems , Moscow : Radio i Svyaz' ; (in Russian) .
   Google Scholar
• Tartakovsky , A. G. ( 1994 ). Asymptotically Minimax Multialternative Sequential Rule for Disorder Detection , Statistics and Control of Random Processes: Proceedings of Steklov Institute of Mathematics , vol. 202 , pp. 229 – 236 , Providence : American Mathematical Society .
   Google Scholar
• Tartakovsky , A. G. ( 1998a ). Asymptotic Optimality of Certain Multihypothesis Sequential Tests: Non-i.i.d. Case , Statistical Inference for Stochastic Processes 1 : 265 – 295 .
   Google Scholar
• Tartakovsky , A. G. ( 1998b ). Extended Asymptotic Optimality of Certain Change-Point Detection Procedures, Technical report/preprint, Center for Applied Mathematical Sciences, University of Southern California .
   Google Scholar
• Tartakovsky , A. G. ( 2005 ). Asymptotic Performance of a Multichart CUSUM Test Under False Alarm Probability Constraint, Proceedings of the 44th IEEE Conference on Decision and Control and the European Control Conference (CDC-ECC'05), 12–15 December 2005 , pp. 320 – 325 , Seville , Spain , Omnipress CD-ROM, ISBN 0-7803-9568-9 .
   Google Scholar
• Tartakovsky , A. G. and Veeravalli , V. V. ( 2002 ). An Efficient Sequential Procedure for Detecting Changes in Multichannel and Distributed Systems, Proceedings of the 5th International Conference on Information Fusion (Fusion 2002) , Annapolis , MD , 8 – 11 July 2002 , vol. 1 , pp. 41 – 48 .
   Google Scholar
• Tartakovsky , A. G. and Veeravalli , V. V. ( 2003 ). Quickest Change Detection in Distributed Sensor Systems, Proceedings of the 6th International Conference on Information Fusion (Fusion 2003) , Cairns , Australia , 8 – 10 July 2003 , pp. 756 – 763 .
   Google Scholar
• Tartakovsky , A. G. and Veeravalli , V. V. ( 2004 ). Change-Point Detection in Multichannel and Distributed Systems with Applications , Applications of Sequential Methodologies , N. Mukhopadhyay , S. Datta , and S. Chattopadhyay , eds., pp. 339 – 370 , New York : Marcel Dekker, Inc .
   Google Scholar
• Tartakovsky , A. G. and Veeravalli , V. V. ( 2005 ). General Asymptotic Bayesian Theory of Quickest Change Detection , Theory of Probability and Its Applications 49 : 458 – 497 .
   Web of Science ®Google Scholar
• Tartakovsky , A. G. and Kim , H. ( 2006 ). Performance of Certain Decentralized Distributed Change Detection Procedures, Proceedings of the 9th International Conference on Information Fusion (Fusion 2006) , Florence , Italy , July 2006 , CD Rom ISBN 0-9721844-6-5 .
   Google Scholar
• Tartakovsky , A. G. and Polunchenko , A. S. ( 2008 ). Quickest Changepoint Detection in Distributed Multisensor Systems under Unknown Parameters, Proceedings of the 11th International Conference on Information Fusion (Fusion 2008), Hyatt Regency Hotel, Cologne , Germany , 30 June–3 July 2008, CD Rom .
   Google Scholar
• Tartakovsky , A. G. , Li , X. R. , and Yaralov , G. ( 2003 ). Sequential Detection of Targets in Multichannel Systems , IEEE Transactions on Information Theory 49 : 425 – 445 .
   Web of Science ®Google Scholar
• Tartakovsky , A. G. , Shah , K. , and Rozovskii , B. L. ( 2005 ). A Nonparametric Multichart CUSUM Test for Rapid Intrusion Detection, Proceedings of Joint Statististical Meetings (JSM) , Minneapolis , MN , 7–11 August 2005 (CD Rom) .
   Google Scholar
• Tartakovsky , A. G. , Rozovskii , B. L. , Blažek , R. , and Kim , H. ( 2006 ). Detection of Intrusions in Information Systems by Sequential Change-Point Methods (with Discussion) , Statistical Methodology 3 : 252 – 340 .
   Google Scholar
• Tsitsiklis , J. N. ( 1993 ). Extremal Properties of Likelihood-Ratio Quantizers , IEEE Transactions on Communications 41 : 550 – 558 .
   Web of Science ®Google Scholar
• Veeravalli , V. V. ( 2001 ). Decentralized Quickest Change Detection , IEEE Transactions on Information Theory 47 : 1657 – 1665 .
   Web of Science ®Google Scholar
• Woodroofe , M. ( 1982 ). Nonlinear Renewal Theory in Sequential Analysis , Philadelphia : SIAM .
   Google Scholar
• Recommended by Wolfgang Schmid
   Google Scholar