Pile-Up Correction in Spectroscopic Signals Using Regularized Sparse Reconstruction

Pile-up is a common problem in high-count-rate gamma spectroscopy. Many techniques have been introduced to overcome this problem. Sparse reconstruction is a recent signal processing method that could be used to solve this problem. In this article, we propose a modified sparse reconstruction method t...

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Veröffentlicht in:IEEE transactions on nuclear science 2020-05, Vol.67 (5), p.858-862
Hauptverfasser: Kafaee, Mahdi, Goodarzi, Mohammad Mohsen
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description Pile-up is a common problem in high-count-rate gamma spectroscopy. Many techniques have been introduced to overcome this problem. Sparse reconstruction is a recent signal processing method that could be used to solve this problem. In this article, we propose a modified sparse reconstruction method to overcome pulse pile-up, especially with ultrahigh count rates. The method uses two regularization terms to compensate for the error caused by an inadequate sampling rate that is called the "verbosity" problem. It significantly improves the pile-up correction process. A scintillation detector pulse train is simulated in different rates by a Monte Carlo approach. Then, the proposed method is validated, and good results are achieved in ultrahigh count rates.
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subjects Compressed sensing
Computer simulation
Delays
Detectors
Dictionaries
Engineering
Engineering, Electrical & Electronic
Error compensation
Gamma spectroscopy
high count rate
Monte Carlo
Nuclear Science & Technology
Photonics
pile-up correction
Reconstruction
Regularization
regularized sparse reconstruction
Science & Technology
Shape
Signal processing
Spectroscopy
Technology
title Pile-Up Correction in Spectroscopic Signals Using Regularized Sparse Reconstruction
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