The detection and estimation of the change point in a disccrete-time stochastic system
作者:
Zachary G. Stoumbos,
期刊:
Stochastic Analysis and Applications
(Taylor Available online 1999)
卷期:
Volume 17,
issue 4
页码: 637-649
ISSN:0736-2994
年代: 1999
DOI:10.1080/07362999908809626
出版商: Marcel Dekker, Inc.
关键词: Bayes Detector;Large Deviations;Likelihood Ratio;Maximum-a-Posteriori Estimator;Measure Transformation;Quality Control;Sequential Detection
数据来源: Taylor
摘要:
A piecewise-constant process containing a single jump is observed under noise in the context of discrete time. The conditional density and maximum a posteriori (MAP) estimator of the jump time as well as the Bayes detector of the jump itself are determined using the powerful measure transformation approach. The Bayes detector provides a convenient sequential detection rule for practical on-line implementation. An asymptotic result for the distribution of the MAP estimator's estimation error and the corresponding convergence rate are derived. This result provides a reference measure of optimal performance for jump-time estimators in discrete-time stochastic systems that does not depend on the jump time's prior distribution
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