• 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