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Nonparametric estimation of mark’s distribution of an exponential shot-noise process

机译:指数散粒过程中标记分布的非参数估计

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In this paper, we consider a nonlinear inverse problem occuring in nuclear science. Gamma rays randomly hit a semiconductor detector which produces an impulse response of electric current. Because the sampling period of the measured current is larger than the mean interarrival time of photons, the impulse responses associated to different gamma rays can overlap: this phenomenon is known as pileup . In this work, it is assumed that the impulse response is an exponentially decaying function. We propose a novel method to infer the distribution of gamma photon energies from the indirect measurements obtained from the detector. This technique is based on a formula linking the characteristic function of the photon density to a function involving the characteristic function and its derivative of the observations. We establish that our estimator converges to the mark density in uniform norm at a polynomial rate. A limited Monte-Carlo experiment is provided to support our findings.
机译:在本文中,我们考虑了核科学中发生的非线性逆问题。伽马射线随机照射到半导体探测器上,该探测器产生电流的脉冲响应。由于测量电流的采样周期大于光子的平均到达时间,因此与不同伽玛射线相关的脉冲响应可能会重叠:这种现象称为堆积。在这项工作中,假定脉冲响应是指数衰减函数。我们提出了一种新颖的方法,可以根据从探测器获得的间接测量结果来推断伽马光子能量的分布。该技术基于将光子密度的特征函数与涉及特征函数及其观测值导数的函数联系起来的公式。我们确定我们的估计量以多项式速率收敛到统一范数中的标记密度。提供了有限的蒙特卡洛实验以支持我们的发现。

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