• DocumentCode
    671794
  • Title

    Analog system modeling based on a double modified complex valued neural network

  • Author

    Luchetta, Antonio ; Manetti, Stefano ; Piccirilli, Maria Cristina

  • Author_Institution
    Dipt. di Ing. dell´Inf. (DINFO), Univ. of Florence, Florence, Italy
  • fYear
    2013
  • fDate
    4-9 Aug. 2013
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    The aim of this work is to present a novel technique for the identification of lumped circuit models of general distributed apparatus and devices. It is based on the use of a double modified complex value neural network. The method is not oriented to a unique class of electromagnetic systems, but it gives a procedure for the complete validation of the approximated lumped model and the extraction of the electrical parameter values. The inputs of the system are the geometrical (and/or manufacturing) parameters of the considered structure, while the outputs are the lumped circuit parameters. The method follows the Frequency Response Analysis (FRA) approach for elaborating the data presented to the network.
  • Keywords
    analogue circuits; frequency response; lumped parameter networks; network synthesis; neural nets; FRA; analog circuit design process; analog system modeling; double modified complex valued neural network; electrical parameter value extraction; electromagnetic systems; frequency response analysis; general distributed apparatus; general distributed devices; geometrical parameters; lumped circuit model identification; Biological neural networks; Frequency measurement; Integrated circuit modeling; Matrix decomposition; Neurons; Training; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2013 International Joint Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-6128-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2013.6707136
  • Filename
    6707136