Optimal sliding-window detector for disruptions in random sequences

Wei Chang, Chris Rorres, Moshe Kam

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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 languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
PublisherPubl by American Automatic Control Council
Number of pages2
ISBN (Print)0780302109, 9780780302105
StatePublished - 1992
Externally publishedYes
EventProceedings of the 1992 American Control Conference - Chicago, IL, USA
Duration: Jun 24 1992Jun 26 1992

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


OtherProceedings of the 1992 American Control Conference
CityChicago, IL, USA

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


Dive into the research topics of 'Optimal sliding-window detector for disruptions in random sequences'. Together they form a unique fingerprint.

Cite this