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A Bayesian Approach to Sequential Change Detection and Isolation Problems

机译:贝叶斯方法顺序变化检测和隔离问题

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摘要

The problem of sequential change detection and isolation under the Bayesian setting is investigated, where the change point is a random variable with a known distribution. A recursive algorithm is proposed, which utilizes the prior distribution of the change point. We show that the proposed decision procedure is guaranteed to control the false alarm probability and the false isolation probability separately under certain regularity conditions, and it is asymptotically optimal with respect to a Bayesian criterion.
机译:研究了贝叶斯设置下顺序变化检测和隔离问题,其中变化点是具有已知分布的随机变量。提出了一种递归算法,其利用改变点的先前分配。我们表明,在某些规则条件下,保证了所提出的决定程序可在某些规则条件下单独控制误报概率和假隔离概率,并且它对贝叶斯标准渐近地是最佳的。

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