• DocumentCode
    1228569
  • Title

    The Minimum Gradient Complexity Control Applied to Sensitivity Extraction of Electromagnetic Devices

  • Author

    Vieira, D.A.G. ; Vasconcelos, J.A. ; Palade, V. ; Caminhas, W.M.

  • Author_Institution
    Dept. of Electr. Eng., Fed. Univ. of Minas Gerais, Belo Horizonte
  • Volume
    44
  • Issue
    6
  • fYear
    2008
  • fDate
    6/1/2008 12:00:00 AM
  • Firstpage
    1114
  • Lastpage
    1117
  • Abstract
    This paper applies the parallel layer perceptron network trained with the minimum gradient method (PLP-MGM) to the problem of indirect sensitivity extraction of electromagnetic devices. The networks trained with the MGM are less dependent of users´ defined parameters, as, for instance, the number of neurons. Some results are presented considering the indirect sensitivity extraction of a loudspeaker magnet assembly unit and an inverse scattering problem, and they show the effectiveness of the proposed approach.
  • Keywords
    computational complexity; electromagnetic devices; gradient methods; inverse problems; sensitivity analysis; electromagnetic devices; indirect sensitivity extraction; inverse scattering problem; loudspeaker magnet assembly unit; minimum gradient complexity control; parallel layer perceptron network; Neural networks; optimization and design; parallel layer perceptron; regularization methods;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/TMAG.2007.915896
  • Filename
    4527018