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1 - Introduction

Published online by Cambridge University Press:  06 July 2010

H. Vincent Poor
Affiliation:
Princeton University, New Jersey
Olympia Hadjiliadis
Affiliation:
Brooklyn College, City University of New York
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Summary

The problem of detecting abrupt changes in the statistical behavior of an observed signal or time series is a classical one, whose provenance dates at least to work in the 1930s on the problem of monitoring the quality of manufacturing processes. In more recent years, this problem has attracted attention in a wide variety of fields, including climate modeling, econometrics, environment and public health, finance, image analysis, medical diagnosis, navigation, network security, neuroscience, other security applications such as fraud detection and counter–terrorism, remote sensing (seismic, sonar, radar, biomedical), video editing, and even the analysis of historical texts. This list, although long, is hardly exhaustive, and other applications can be found, for example, in. These cited references only touch the surface of a very diverse and vibrant field, in which this general problem is known variously as statistical change detection, change–point detection, or disorder detection.

Many of these applications, such as those in image analysis, econometrics, or the analysis of historical texts, involve primarily off–line analyses to detect a change in statistical behavior during a pre–specified frame of time or space. In such problems, it is of interest to estimate the occurrence time of a change, and to identify appropriate statistical models before and after the change. However, it is not usually an objective of these applications to perform these functions in real time.

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Publisher: Cambridge University Press
Print publication year: 2008

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  • Introduction
  • H. Vincent Poor, Princeton University, New Jersey, Olympia Hadjiliadis, Brooklyn College, City University of New York
  • Book: Quickest Detection
  • Online publication: 06 July 2010
  • Chapter DOI: https://doi.org/10.1017/CBO9780511754678.003
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  • Introduction
  • H. Vincent Poor, Princeton University, New Jersey, Olympia Hadjiliadis, Brooklyn College, City University of New York
  • Book: Quickest Detection
  • Online publication: 06 July 2010
  • Chapter DOI: https://doi.org/10.1017/CBO9780511754678.003
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Introduction
  • H. Vincent Poor, Princeton University, New Jersey, Olympia Hadjiliadis, Brooklyn College, City University of New York
  • Book: Quickest Detection
  • Online publication: 06 July 2010
  • Chapter DOI: https://doi.org/10.1017/CBO9780511754678.003
Available formats
×