Optimal sliding-window detector for disruptions in random sequences

Wei Chang; Chris Rorres; Moshe Kam

doi:10.23919/acc.1992.4792503

Optimal sliding-window detector for disruptions in random sequences

Wei Chang, Chris Rorres, Moshe Kam

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The detection of instants of change in random process properties, a problem with a variety of applications in technical and medical diagnostics, control, and image processing, is considered. The focus in this study is on the detection of a jump change in the mean and/or variance of an observed random sequence. The problem is to detect the jump as quickly as possible after its occurrence while avoiding an excessive false alarm rate (i.e. declaring a change before it occurs). For this purpose, the Neyman-Pearson criterion for the design of a disruption detector is used. An optimal design formula is derived for limiting cases. Using a Neyman-Pearson criterion, the designer can determine an optimal window size and an optimal detector sensitivity.

Original language	English (US)
Title of host publication	Proceedings of the American Control Conference
Publisher	Publ by American Automatic Control Council
Pages	2121-2122
Number of pages	2
ISBN (Print)	0780302109, 9780780302105
DOIs	https://doi.org/10.23919/acc.1992.4792503
State	Published - 1992
Externally published	Yes
Event	Proceedings of the 1992 American Control Conference - Chicago, IL, USA Duration: Jun 24 1992 → Jun 26 1992

Publication series

Name	Proceedings of the American Control Conference
Volume	3
ISSN (Print)	0743-1619

Other

Other	Proceedings of the 1992 American Control Conference
City	Chicago, IL, USA
Period	6/24/92 → 6/26/92

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.23919/acc.1992.4792503

Cite this

@inproceedings{45e9368ce870410eb7841e98551413bc,

title = "Optimal sliding-window detector for disruptions in random sequences",

abstract = "The detection of instants of change in random process properties, a problem with a variety of applications in technical and medical diagnostics, control, and image processing, is considered. The focus in this study is on the detection of a jump change in the mean and/or variance of an observed random sequence. The problem is to detect the jump as quickly as possible after its occurrence while avoiding an excessive false alarm rate (i.e. declaring a change before it occurs). For this purpose, the Neyman-Pearson criterion for the design of a disruption detector is used. An optimal design formula is derived for limiting cases. Using a Neyman-Pearson criterion, the designer can determine an optimal window size and an optimal detector sensitivity.",

author = "Wei Chang and Chris Rorres and Moshe Kam",

year = "1992",

doi = "10.23919/acc.1992.4792503",

language = "English (US)",

isbn = "0780302109",

series = "Proceedings of the American Control Conference",

publisher = "Publ by American Automatic Control Council",

pages = "2121--2122",

booktitle = "Proceedings of the American Control Conference",

note = "Proceedings of the 1992 American Control Conference ; Conference date: 24-06-1992 Through 26-06-1992",

}

Chang, W, Rorres, C & Kam, M 1992, Optimal sliding-window detector for disruptions in random sequences. in Proceedings of the American Control Conference. Proceedings of the American Control Conference, vol. 3, Publ by American Automatic Control Council, pp. 2121-2122, Proceedings of the 1992 American Control Conference, Chicago, IL, USA, 6/24/92. https://doi.org/10.23919/acc.1992.4792503

TY - GEN

T1 - Optimal sliding-window detector for disruptions in random sequences

AU - Chang, Wei

AU - Rorres, Chris

AU - Kam, Moshe

PY - 1992

Y1 - 1992

N2 - The detection of instants of change in random process properties, a problem with a variety of applications in technical and medical diagnostics, control, and image processing, is considered. The focus in this study is on the detection of a jump change in the mean and/or variance of an observed random sequence. The problem is to detect the jump as quickly as possible after its occurrence while avoiding an excessive false alarm rate (i.e. declaring a change before it occurs). For this purpose, the Neyman-Pearson criterion for the design of a disruption detector is used. An optimal design formula is derived for limiting cases. Using a Neyman-Pearson criterion, the designer can determine an optimal window size and an optimal detector sensitivity.

AB - The detection of instants of change in random process properties, a problem with a variety of applications in technical and medical diagnostics, control, and image processing, is considered. The focus in this study is on the detection of a jump change in the mean and/or variance of an observed random sequence. The problem is to detect the jump as quickly as possible after its occurrence while avoiding an excessive false alarm rate (i.e. declaring a change before it occurs). For this purpose, the Neyman-Pearson criterion for the design of a disruption detector is used. An optimal design formula is derived for limiting cases. Using a Neyman-Pearson criterion, the designer can determine an optimal window size and an optimal detector sensitivity.

UR - http://www.scopus.com/inward/record.url?scp=0026960932&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026960932&partnerID=8YFLogxK

U2 - 10.23919/acc.1992.4792503

DO - 10.23919/acc.1992.4792503

M3 - Conference contribution

AN - SCOPUS:0026960932

SN - 0780302109

SN - 9780780302105

T3 - Proceedings of the American Control Conference

SP - 2121

EP - 2122

BT - Proceedings of the American Control Conference

PB - Publ by American Automatic Control Council

T2 - Proceedings of the 1992 American Control Conference

Y2 - 24 June 1992 through 26 June 1992

ER -

Optimal sliding-window detector for disruptions in random sequences

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All Science Journal Classification (ASJC) codes

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