Sequential Detection under Markov Dependence
نویسنده
چکیده
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.
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تاریخ انتشار 1999