• DocumentCode
    3112514
  • Title

    E.M. Inverse Scattering and Multi-Layer Perceptrons: Towards the automatic reconstruction of buried layers´ properties

  • Author

    Caorsi, Salvatore ; Stasolla, Mattia

  • Author_Institution
    Dept. of Electron., Univ. of Pavia, Pavia, Italy
  • fYear
    2010
  • fDate
    16-19 Aug. 2010
  • Firstpage
    1000
  • Lastpage
    1003
  • Abstract
    The goal of this paper is a preliminary robustness assessment of a recently published ANN-based algorithm for the evaluation of subsurface layers´ properties. In particular, the analysis will focus on the dependency of overall performances on the training set dimensions and the neural networks capabilities of managing numerical errors.
  • Keywords
    buried layers; electromagnetic wave scattering; ground penetrating radar; multilayer perceptrons; neural nets; ANN-based algorithm; EM inverse scattering; automatic reconstruction; buried layers property; electromagnetic wave scattering; multilayer perceptrons; neural network capability; robustness assessment; subsurface layer property; training set dimension; Artificial neural networks; Data models; Error analysis; Ground penetrating radar; Permittivity; Robustness; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electromagnetic Theory (EMTS), 2010 URSI International Symposium on
  • Conference_Location
    Berlin
  • Print_ISBN
    978-1-4244-5155-5
  • Electronic_ISBN
    978-1-4244-5154-8
  • Type

    conf

  • DOI
    10.1109/URSI-EMTS.2010.5637142
  • Filename
    5637142