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Non-Parametric Decompounding of Pulse Pile-Up Under Gaussian Noise With Finite Data Sets | IEEE Journals & Magazine | IEEE Xplore

Non-Parametric Decompounding of Pulse Pile-Up Under Gaussian Noise With Finite Data Sets


Abstract:

A novel estimator is proposed for estimating the energy distribution of photons incident upon a detector in X-ray spectroscopic systems. It is specifically designed for c...Show More

Abstract:

A novel estimator is proposed for estimating the energy distribution of photons incident upon a detector in X-ray spectroscopic systems. It is specifically designed for count-rate regimes where pulse pile-up is an issue. A key step in the derivation of the estimator is the novel reformulation of the problem as a decompounding problem of a compound Poisson process. A non-parametric decompounding algorithm is proposed for pile-up correction with finite-length data sets. Non-parametric estimation typically includes appropriately choosing a `kernel bandwidth'. Simulations demonstrate our data-driven bandwidth selection is close to optimal, and outperforms asymptotic-based selection in the typical regions of interest to spectroscopic applications. Non-parametric approaches are particularly useful when the shape of the detector response varies with each interaction. The method exhibits similar accuracy to other state-of-the-art non-parametric methods, while being much faster to compute.
Published in: IEEE Transactions on Signal Processing ( Volume: 68)
Page(s): 2114 - 2127
Date of Publication: 18 March 2020

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