• DocumentCode
    2622217
  • Title

    A neural network approach for identification of EM field sources: analysis of PCB configurations

  • Author

    D´Amore, M. ; Morriello, A. ; Sarto, M.S.

  • Author_Institution
    Dept. of Electr. Eng., Rome Univ., Italy
  • Volume
    2
  • fYear
    1998
  • fDate
    24-28 Aug 1998
  • Firstpage
    664
  • Abstract
    The neural network approach is applied to recognize EM emission sources of PCB configurations, with or without attached cables. The learning process is accomplished by using computed spectra of the radiated field from PCBs having different configurations. The trained neural network is then applied to the identification of PCB layouts from radiated emission measurements
  • Keywords
    circuit analysis computing; electromagnetic compatibility; electromagnetic interference; learning (artificial intelligence); neural nets; printed circuit layout; EM emission sources recognition; PCB configurations analysis; PCB layouts identification; learning process; neural network approach; radiated emission measurements; radiated field spectra; Coaxial cables; Electromagnetic fields; Electromagnetic measurements; Electromagnetic radiation; Equations; Microstrip; Neural networks; Predictive models; Radiofrequency identification; Transmission line matrix methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electromagnetic Compatibility, 1998. 1998 IEEE International Symposium on
  • Conference_Location
    Denver, CO
  • Print_ISBN
    0-7803-5015-4
  • Type

    conf

  • DOI
    10.1109/ISEMC.1998.750276
  • Filename
    750276