Paper Info
Title
An EM approach to mineral analysis using natural gamma rays
Abstract
We describe here a method for the analysis of materials on a conveyor belt using the natural gamma spectra collected with a BGO (Bismuth Germanate) gamma ray detector. This detector collects gamma ray emissions from the Potassium (K), Uranium (U), and Thorium (Th) atoms in the materials. Based on these data, and using a Poisson model for the data generation, a statistical model is proposed and an approximate maximum likelihood (ML) technique based on the expectation-maximization (EM) algorithm is then used to estimate the amount of each of the three elements in the material. The statistical model is further refined to incorporate parameters of drift in the detector and an estimation technique for this is developed and tested against real data. The Cramer-Rao lower bounds for the estimators are calculated.
Year
DOI
Venue
2009
10.1016/j.dsp.2009.04.001
Digital Signal Processing
Keywords
Field
DocType
em approach,poisson processes,natural gamma ray,gamma-ray detectors,gamma ray emission,gamma ray detector,data generation,expectation-maximization,natural gamma spectrum,mineral analysis,statistical model,poisson model,estimation technique,bismuth germanate,maximum likelihood estimation,statistical signal processing,cramer-rao lower bound,expectation maximization,maximum likelihood,maximum likelihood estimate,potassium,poisson process,lower bound,em algorithm,gamma ray
Mathematical optimization,Bismuth germanate,Expectation–maximization algorithm,Spectral line,Statistical model,Gamma ray,Maximum likelihood sequence estimation,Detector,Mathematics,Estimator
Journal
Volume
Issue
ISSN
19
5
Digital Signal Processing
Citations 
PageRank 
References 
1
0.35
2
Authors
6
Name
Order
Citations
PageRank
B. Moran111121.09
Du Q. Huynh231221.77
Xuezhi Wang3254.53
Michael Edwards410.69
Andrew Harris510.69
Barbara F. La Scala65411.26