Sequential Detection of Transient Changes

This article addresses the transient change detection problem. It is assumed that a change occurs at an unknown (but nonrandom) change-point and the duration of post-change period is finite and known. A latent detection-that is, a detection that occurs after signal disappearance-is considered as a m...

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Published inSequential analysis Vol. 31; no. 4; pp. 528 - 547
Main Authors Guépié, Blaise Kévin, Fillatre, Lionel, Nikiforov, Igor
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis Group 01.10.2012
Taylor & Francis Ltd
Taylor & Francis
Subjects
Algorithms
Change detection
Computer Science
Criteria
Decision theory
Detection algorithms
Drinking water
Environmental monitoring
Failure detection
False alarms
Mathematical analysis
Monitoring
Optimization
Probability
Signal and Image Processing
Signal detection
Signaling
Statistical analysis
Transient signals
Upper bounds
Water pollution
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Abstract This article addresses the transient change detection problem. It is assumed that a change occurs at an unknown (but nonrandom) change-point and the duration of post-change period is finite and known. A latent detection-that is, a detection that occurs after signal disappearance-is considered as a missed detection. A new optimality criterion adapted to the detection of transient changes involves the minimization of the worst-case probability of missed detection under constraint on the false alarm rate for a given period. A suboptimal sequential transient change detection algorithm is proposed. It is based on a window-limited cumulative sum (CUSUM) test. An upper bound for the worst-case probability of missed detection and a lower and an upper bound for the false alarm rate are proposed. Based on these bounds, the window-limited CUSUM test is optimized with respect to the proposed criterion. The developed algorithm and theoretical findings are applied to drinking water distribution network monitoring.
AbstractList This article addresses the transient change detection problem. It is assumed that a change occurs at an unknown (but nonrandom) change-point and the duration of post-change period is finite and known. A latent detection-that is, a detection that occurs after signal disappearance-is considered as a missed detection. A new optimality criterion adapted to the detection of transient changes involves the minimization of the worst-case probability of missed detection under constraint on the false alarm rate for a given period. A suboptimal sequential transient change detection algorithm is proposed. It is based on a window-limited cumulative sum (CUSUM) test. An upper bound for the worst-case probability of missed detection and a lower and an upper bound for the false alarm rate are proposed. Based on these bounds, the window-limited CUSUM test is optimized with respect to the proposed criterion. The developed algorithm and theoretical findings are applied to drinking water distribution network monitoring.
This article addresses the transient change detection problem. It is assumed that a change occurs at an unknown (but nonrandom) change-point and the duration of post-change period is finite and known. A latent detection -- that is, a detection that occurs after signal disappearance -- is considered as a missed detection. A new optimality criterion adapted to the detection of transient changes involves the minimization of the worst-case probability of missed detection under constraint on the false alarm rate for a given period. A suboptimal sequential transient change detection algorithm is proposed. It is based on a window-limited cumulative sum (CUSUM) test. An upper bound for the worstcase probability of missed detection and a lower and an upper bound for the false alarm rate are proposed. Based on these bounds, the window-limited CUSUM test is optimized with respect to the proposed criterion. The developed algorithm and theoretical findings are applied to drinking water distribution network monitoring.
Author Nikiforov, Igor
Fillatre, Lionel
Guépié, Blaise Kévin
Author_xml – sequence: 1
  givenname: Blaise Kévin
  surname: Guépié
  fullname: Guépié, Blaise Kévin
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  givenname: Lionel
  surname: Fillatre
  fullname: Fillatre, Lionel
  organization: Institut Charles Delaunay, LM2S , Université de technologie de Troyes, UMR STMR-CNRS
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  givenname: Igor
  surname: Nikiforov
  fullname: Nikiforov, Igor
  email: nikiforov@utt.fr
  organization: Institut Charles Delaunay, LM2S , Université de technologie de Troyes, UMR STMR-CNRS
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Snippet This article addresses the transient change detection problem. It is assumed that a change occurs at an unknown (but nonrandom) change-point and the duration...
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SubjectTerms Algorithms
Change detection
Computer Science
Criteria
Decision theory
Detection algorithms
Drinking water
Environmental monitoring
Failure detection
False alarms
Mathematical analysis
Monitoring
Optimization
Probability
Signal and Image Processing
Signal detection
Signaling
Statistical analysis
Transient signals
Upper bounds
Water pollution
Title Sequential Detection of Transient Changes
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