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On-line statistical processing of radiation detector pulse trains with time-varying count rates

机译:时变计数率的辐射探测器脉冲序列的在线统计处理

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Statistical analysis is of primary importance for the correct interpretation of nuclear measurements, due to the inherent random nature of radioactive decay processes. This paper discusses the application of statistical signal processing techniques to the random pulse trains generated by radiation detectors. The aims of the presented algorithms are: (i) continuous, on-line estimation of the underlying time-varying count rate θ(t) and its first-order derivative dθ/dt; (ii) detection of abrupt changes in both of these quantities and estimation of their new value after the change point. Maximum-likelihood techniques, based on the Poisson probability distribution, are employed for the on-line estimation of θ and dθ/dt. Detection of abrupt changes is achieved on the basis of the generalized likelihood ratio statistical test. The properties of the proposed algorithms are evaluated by extensive simulations and possible applications for on-line radiation monitoring are discussed.
机译:由于放射性衰变过程的固有随机性,统计分析对于正确解释核测量值至关重要。本文讨论了统计信号处理技术在辐射探测器产生的随机脉冲序列中的应用。所提出算法的目的是:(i)对时变计数率θ(t)及其一阶导数dθ/ dt进行连续在线估计。 (ii)检测这两个量的突然变化,并估计变化点之后的新值。基于泊松概率分布的最大似然技术可用于θ和dθ/ dt的在线估计。突变的检测是基于广义似然比统计检验实现的。通过广泛的仿真评估了所提出算法的性能,并讨论了在线辐射监测的可能应用。

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