On a sparse regression algorithm for activity estimation in Gamma spectrometry

Autor: Tom Trigano, Y. Mashiach, Yann Sepulcre, M. Tal
Rok vydání: 2010
Předmět:
Zdroj: 2010 IEEE 26-th Convention of Electrical and Electronics Engineers in Israel.
DOI: 10.1109/eeei.2010.5661973
Popis: The aim of Gamma spectrometry is to identify radioactive sources and their activities by means of the analysis of the photon energy received by a detector. When the activity of the source is high, a physical phenomenon known as pileup distorts the energy spectra and introduces a significant bias to the standard estimators of the source activities. We provide in this paper a fast algorithm which significantly improves the precision of the counting rate activity, based on a sparse representation of the time signal. Experiments on simulations and real datasets show the efficiency of the proposed approach.
Databáze: OpenAIRE