DocumentCode
2829075
Title
Fitting Multiple Alpha Peaks Using Neural Network Techniques
Author
Miranda, Javier ; Baeza, Antonio ; Guillen, Jose ; Utrero, Rosa M Pérez
Author_Institution
Dipt. Fis. Aplic., Univ. de Extremadura, Caceres, Spain
fYear
2009
fDate
Nov. 30 2009-Dec. 2 2009
Firstpage
1296
Lastpage
1300
Abstract
Despite the sophistication of today´s radiochemical separation techniques, it often occurs that the peaks in the spectra of ¿-emitting radioactive samples partially overlap. We here demonstrate the usefulness of a procedure based on a neural network, a multilayer perceptron with backpropagation training method, trained with isolated alpha peaks of environmental samples in resolving such partially overlapping alpha peaks and in predicting the activities of the ¿-emitters detected.
Keywords
backpropagation; chemical engineering computing; multilayer perceptrons; radiochemistry; backpropagation training method; environmental samples; multilayer perceptron; multiple alpha peak fitting; neural network techniques; radiochemical separation techniques; Alpha particles; Backpropagation; Detectors; Intelligent networks; Intelligent systems; Multi-layer neural network; Multilayer perceptrons; Neural networks; Shape; Tail; alpha; analysis; network; neural; overlap; peak; radiactivity; spectrum;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on
Conference_Location
Pisa
Print_ISBN
978-1-4244-4735-0
Electronic_ISBN
978-0-7695-3872-3
Type
conf
DOI
10.1109/ISDA.2009.144
Filename
5364017
Link To Document