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Sequential Detection Under Markov Dependence (1999)
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BibTeX
@MISC{Chandramouli99sequentialdetection,
author = {R. Chandramouli and N. Ranganathan},
title = {Sequential Detection Under Markov Dependence},
year = {1999}
}
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Abstract
In this paper, we investigate a sequential test for binary hypothesis testing for stationary, first-order Markov dependent observations in steady state. Wald's first and second lemmas are generalized. For a Markov chain with symmetric transition probability matrix the average sample number required by the test to decide a hypothesis is derived. Numerical analysis shows that accounting for a positive correlation in the observations results in a significant decrease in the average sample number for fixed error probabilities.
Keyphrases
markov dependence sequential detection average sample number numerical analysis markov chain symmetric transition probability first-order markov dependent observation sequential test fixed error probability significant decrease binary hypothesis second lemma steady state observation result positive correlation
