Abstract

Since radionuclides have unique characteristic gamma-ray spectra, usually maintained as a set of (energy, counts/energy) ordered pairs, an explicit functional representation would be indisputably useful. In this paper, the Gamma Detector Response and Analysis Software has been used to simulate the gamma-ray spectra as it would be collected by an NaI detector for a set of 70 radionuclides. Gaussian radial basis function (RBF) networks that offer simple, closed-form expressions are then trained to represent each of these spectra. Hence, a library consisting of 70 RBF networks for the corresponding radionuclides has been built. The presence of these library-contained radionuclides in a given gamma-ray spectrum of an unknown source is identified by an algorithm that employs a linear combination of the library spectra to approximate the unknown spectrum. The combination coefficients are then determined by minimizing the squared deviation error function under convexity constraints.

摘要

由于放射性核素具有独特的特征性伽马射线光谱，通常保持为一组（能量，计数/能量）有序对，因此明确的功能表示无疑是有用的。在本文中，伽玛探测器响应和分析软件已被用来模拟由NaI探测器收集的70个放射性核素的伽玛射线谱。然后训练提供简单，封闭形式的表达式的高斯径向基函数（RBF）网络来表示这些光谱中的每一个。因此，已经建立了由70个RBF网络组成的对应放射性核素的库。通过使用库光谱的线性组合来近似未知光谱的算法，可以识别未知源的给定伽马射线光谱中这些库包含的放射性核素的存在。然后，通过在凸度约束下最小化平方偏差误差函数来确定组合系数。