DocumentCode
2055685
Title
Information bounds and asymptotically optimal procedures for detecting changes in decentralized decision systems
Author
Mei, Yajun
Author_Institution
Fred Hutchinson Cancer Res. Center, Seattle, WA, USA
fYear
2004
fDate
27 June-2 July 2004
Firstpage
249
Abstract
This paper develops sharp information-theoretic bounds and offers asymptotically optimal procedures for decentralized quickest change detection under different scenarios. A lower bound of the detection delay is developed in the system with limited local memory and it is proved that the decentralised CUSUM procedure with a monotone likelihood ratio quantiser (MLRQ) defined is asymptotically optimal.
Keywords
delays; information theory; multivariable systems; sensors; asymptotically optimal procedures; decentralized decision systems; detection delay; local memory; monotone likelihood ratio quantiser; sharp information-theoretic bounds; Cancer detection; Delay effects; Density functional theory; Exponential distribution; Feedback; Information theory; Sensor fusion; Sensor systems; Surveillance; Wireless communication;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on
Print_ISBN
0-7803-8280-3
Type
conf
DOI
10.1109/ISIT.2004.1365287
Filename
1365287
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