
Accession Number : ADA309507
Title : Robust, Distributed, and Adaptive Quickest Detection Procedures.
Descriptive Note : Technical rept. Sep 91Jun 94,
Corporate Author : PRINCETON UNIV NJ
Personal Author(s) : Crow, R. W. ; Schwartz, S. C.
PDF Url : ADA309507
Report Date : JUN 1995
Pagination or Media Count : 214
Abstract : This dissertation focuses on sequential techniques for detecting a change, or disorder, in the statistics of a random process. First, the minimax robust quickest detector is derived for the case when the underlying noise models are only partially known. It is shown that when the robust processor is used, the minimax asymptotic performance measure is equal to the KullbackLeibler divergence, and that the least favorable densities are those that minimize this quantity. The robust quickest detector is also determined for the weak signal case, and we show an equivalence between the performance measure, the classical efficacy, and Fisher's information. Performance curves are given to show the gain available when robustness is built into the procedure. The robust quickest detector is also derived under mean and covariance uncertainty for a multivariate Gaussian noise process. It is shown that the robust processor is exactly the robust discretetime matched filter, which has been studied previously. Expressions for the asymptotic performance are derived, and particular solutions are presented for several uncertainty classes. Performance curves are provided to illustrate the tradeoffs when there is a mismatch between the assumed and actual levels of uncertainty. The applicability of the robust procedure to nonGaussian noise is also discussed.
Descriptors : *MATHEMATICAL MODELS, *MULTIVARIATE ANALYSIS, *STATISTICAL PROCESSES, ALGORITHMS, SIGNAL PROCESSING, UNCERTAINTY, OPTIMIZATION, DISTRIBUTED DATA PROCESSING, TIME DEPENDENCE, MAXIMUM LIKELIHOOD ESTIMATION, STATISTICAL TESTS, PROBABILITY DISTRIBUTION FUNCTIONS, RANDOM VARIABLES, STATISTICAL DATA, SIGNAL TO NOISE RATIO, GAUSSIAN NOISE, ORDER DISORDER TRANSFORMATIONS, MONTE CARLO METHOD, STATISTICAL SAMPLES, NONPARAMETRIC STATISTICS, DISCRETE DISTRIBUTION, SYSTEMS ANALYSIS, COVARIANCE, BAYES THEOREM, TRADE OFF ANALYSIS, ORDER STATISTICS, MATCHED FILTERS, MARKOV PROCESSES, POISSON RATIO.
Subject Categories : Statistics and Probability
Operations Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE