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首页> 外文期刊>IEEE Transactions on Signal Processing >Sparse Reconstruction Algorithm for Nonhomogeneous Counting Rate Estimation
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Sparse Reconstruction Algorithm for Nonhomogeneous Counting Rate Estimation

机译：非均匀计数率估计的稀疏重建算法

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摘要

One of the main objectives of nuclear spectroscopy is the estimation of the counting rate of unknown radioactive sources. Recently, we proposed an algorithm based on a sparse reconstruction of the time signal in order to estimate precisely this counting rate, under the assumption that it remained constant over time. Computable bounds were obtained to quantify the performances. This approach, based on a postprocessed approach of a non-negative sparse regression of the time signal, performed well even when the activity of the source was high. The purpose of this paper is to present an extension of the previous method for an activity varying over time. It relies on the same preliminary sparse reconstruction. However, the postprocessed and plug-in steps are made differently to fit the nonhomogeneous framework. The adapted bounds are presented, and results on simulations illustrate the advantages and limitations of this method.
机译：核光谱学的主要目标之一是估计未知放射源的计数率。最近，我们提出了一种基于时间信号的稀疏重构的算法，以便精确估计此计数率，并假设该计数率随时间保持恒定。获得可计算边界以量化性能。该方法基于时间信号的非负稀疏回归的后处理方法，即使在源的活动较高的情况下也能很好地执行。本文的目的是提出针对活动随时间变化的先前方法的扩展。它依赖于相同的初步稀疏重建。但是，后处理步骤和插件步骤的制作方式有所不同，以适应非均匀框架。提出了适应范围，并且仿真结果说明了该方法的优点和局限性。

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