Detection of abrupt changes in signals and dynamical systems : Some statistical aspects

  • A. Benveniste
  • M. Basseville
Session 4 Detection Of Changes In Systems
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 62)


The aim of this paper is to present to the signal processing community some points of this detection problem, with a particular emphasis on the statistical aspects, leaving out the system theoretic aspects, which are of great importance in the control context, or, more generally, in the case of multichannel signal processing. A briel overview is presented of some of the issues developped in the CNRS - conference : "Détection de ruptures dans les Modèles Dynamiques de Signaux et Systèmes" held in Paris, on March 21–22 — (CNRS - 1984).


Detection Problem Jump Time Control Context Generalize Likelihood Ratio Geophysical Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    U. Appel, A. Brandt, (1983). "Adaptive sequential segmentation of piecewise stationary time series"., Information Sciences, Vol. 28, April.Google Scholar
  2. [2]
    M. Basseville, (1981) "Edge detection using sequential methods for change in level, part II: sequential detection of change in mean", IEEE-ASSP — 29 No 1 32–50Google Scholar
  3. [3]
    M. Basseville, B. Espiau, J. Gasnier, (1981)., "Edge detection using sequential methods for change in level, part I: a sequential edge detection algorithm"., IEEE-ASSP — 29 no 1, 24–31.Google Scholar
  4. [4]
    M. Basseville, A. Benveniste, (1983-a)., "Design and comparative study of some sequential jump detection algorithms for digital signals"., IEEE-ASSP — 31, No3, June 1983.Google Scholar
  5. [5]
    M. Basseville, A Benveniste, (1983-b)., "Sequential detection of abrupt changes in spectral characteristics of digital signals"., IEEE-IT — 24, Sept. 1983Google Scholar
  6. [6]
    G.K Bhattacharya, R.A Johnson, (1968).n "Non parametric tests for shift at an unknown time point"., Ann. Math. Statistics, Vol. 39, no 5, 1731–1743.Google Scholar
  7. [7]
    G. Bodenstein, H.M. Praetorius, (1977)., "Feature extraction form the encephalogram by adaptive segmentation"., Proc. IEEE, Vol. 65, 642–652.Google Scholar
  8. [8]
    E.Y Chow, A.S Willsky, (1984)., "Analytical redundancy and the design of robust failure detection systems"., to appear, IEEE-AC, 1984.Google Scholar
  9. [9]
    R.B. Davies, (1973)., "Asymptotic inference in stationary gaussian time series"., Adv. Appl. Proba. 5, 469–497.Google Scholar
  10. [10]
    J.C. Deckert, M.N Desai, J.J. Deyst, A.S. Willsky, (1977)., "F8 DFWB sensor failure identification using analytic redundancy"., IEEE-AC — 22, No 5, 725–803.Google Scholar
  11. [11]
    J. Deshayes, D. Picard, (1982)., "Tests de rupture de régression, comparaison asymptotique"., Teoryia Ver. Prim. 95–108.Google Scholar
  12. [12]
    J. Deshayes, D. Picard, (1983)., "Principe d'invariance sur les processus de vraisemblance"., Thèse d'état, Université d'Orsay, France, to appear 1984 in annales de l'institut Henri Poincaré.Google Scholar
  13. [13]
    A.H. Gray, J.D. Markel, (1976)., "Distances measures for speech processing"., IEEE-ASSP — 24, No 5, 380–391.Google Scholar
  14. [14]
    W.G.S. Hines, (1976)., "A simple monitor of a system with sudden parameter changes"., IEEE-IT — 22, No 2, 210–216.Google Scholar
  15. [15]
    D.V. Hinkley, (1971)., "Inference about the change-point from cumulative sumtests"., Biometrika, vol. 58, 509–523.Google Scholar
  16. [16]
    I.A. Ibragimov, R.Z. Khas'minskii, (1972). "Asymptotic Behavior of Statistical Estimators in the Smooth case-I. Study of the Likelihood Ratio". Theory of Proba. and Appl. Vol 17 no 3. 445–462.Google Scholar
  17. [17]
    B. Kedem, E. Slud, (1981)., "On goodness of fit of time series models, an application of high order crossing"., Biometrika, Vol. 68, No 2, 551–556.Google Scholar
  18. [18]
    B. Kedem, E. Slud, (1982)., "Time series discrimination by higher order crossings"., Annals of Statistics, Vol.10, No 3, 786–794.Google Scholar
  19. [19]
    I.V. Nikiforov, (1979)., "Cumulative sums for detection of changes in random process characteristics"., Autom. Remote control, Vol. 40, No 2, 192–202Google Scholar
  20. [20]
    I.V. Nikiforov, (1980)., "Modification and analysis of the cumulative sum procedure"., Automatika i Telemekanikha, Vol. 41, No 9, 74–80.Google Scholar
  21. [21]
    I.V. Nikiforov, (1983)., Sequential detection of abrupt changes in time series properties; Nauka, Mascow.Google Scholar
  22. [22]
    E.S. Page, (1954)., "Continuous inspection schemes"., Biometrika, Vol. 41, 100–114.Google Scholar
  23. [23]
    G.G. Roussas, (1972)., Contiguity of probability measures, some applications in statistics., Cambridge University press.Google Scholar
  24. [24]
    J. Segen, A.C. Sanderson, (1980)., "Detecting changes in time series"., IEEE-IT 26, No 2, 249–255.Google Scholar
  25. [25]
    A.S. Willsky, (1976)., "A survey of design methods for failure detection in dynamic systems"., Automatica, Vol. 12, 601–611.Google Scholar
  26. [26]
    A.S. Willsky, H.L. Jones, (1976)., "a generalized likelihood ratio approach to the detection and estimation of jumps in linear systems"., IEEE-AC — 21 No 1, 108–112.Google Scholar
  27. [27]
    CNRS-Conference: "Détection de Ruptures dans les Modèles Dynamiques de Signaux et Systèmes". Paris March 21–22, 1984.Google Scholar
  28. [C1]
    R. André, M. Basseville, A. Benveniste: "un Exemple de Segmentation Temps-Réel du Signal de Parole".Google Scholar
  29. [C2]
    M. Basseville: "Détection Séquentielle de Sauts de Moyenne".Google Scholar
  30. [C3]
    M. Basseville: "Exemples d'Utililation de l'Algorithme GLR."Google Scholar
  31. [C4]
    M. Basseville: "Quelques Algorithmes de Détection de Changements de Caractéristiques Spectrales Utilisés en Traitement du Signal".Google Scholar
  32. [C5]
    J. Deshayes, D. Picard: "Méthodes Globales de test et d'Estimation de Ruptures: Points de Vue Asymptotiques".Google Scholar
  33. [C6]
    I.V. Nikiforov: "Sequential Detection of changes in Times Series Properties Based on a Modified Cumulative Sum Algorithm".Google Scholar
  34. [C7]
    D. Picard, J. Deshayes: "Comment utiliser les Statistiques de Vraisemblance dans un Problème de Rupture".Google Scholar
  35. [C9]
    A.S. Willsky, E.Y. Chow, X.C. Lou, G.C. Verghese: "Redundancy Relations and Robust Failure Detection".Google Scholar
  36. [C10]
    A.S. Willsky, P.C Doerschuk, R.R. Tenney; "Estimation — Based Approaches to Rhythm Analysis in Electrocardiograms".Google Scholar
  37. [C8]
    A.S. Willsky: "Detection of Abrupt changes in Dynamic Systems".Google Scholar

Copyright information

© Springer-Verlag 1984

Authors and Affiliations

  • A. Benveniste
    • 1
  • M. Basseville
    • 2
  1. 1.IRISA/INRIA Campus Universitaire de BeaulieuRennes CédexFrance
  2. 2.IRISA/CNRS Campus Universitaire de BeaulieuRennes CédexFrance

Personalised recommendations