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具有误报概率界的动态抽样正态均值变化检测AI 解读

We show that when dynamic sampling is feasible, there exist surveillance schemes for which the probability of a false alarm is bounded and which have a bounded expected delay when detecting a (true) change. In the case of detecting a change of a normal mean, we probe optimality and suggest procedures. These procedures compare favorably to those having a fixed sampling rate which have been developed for an expectation constraint on the average run length until a false alarm.

检测分布变化的动态抽样方法AI 解读

The problem of detecting a change in drift of Brownian motion is considered in the Bayesian framework with the time of change having a (prior) exponential distribution. To the well known problem of finding an optimal stopping rule for "declaring a change," we add the option of continuously controlling the sampling rates--resulting in controlling the variance coefficient of the process. The combined problem of finding an optimal rate function (dynamic sampling) together with…