• DocumentCode
    2733770
  • Title

    A Recurrent Neural Networks Based Modeling Approach for Internal Circuits of Electronic Devices

  • Author

    Aimin, Zhang ; Hang, Zhang ; Hong, Li ; Degui, Chen

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., Xi´´an
  • fYear
    2009
  • fDate
    12-16 Jan. 2009
  • Firstpage
    293
  • Lastpage
    296
  • Abstract
    In this paper, a modeling approach is developed for internal circuits of electronic devices. Two types of recurrent neural networks (RNN), both with and without time sequence, are trained to learn the dynamic responses of interferences in frequency and time domain respectively. After training, the RNN model provides fast evaluation of interference responses of the original internal circuits, which is useful for electromagnetic susceptibility (EMS) analysis and optimization of electronic devices. Two examples are provided to demonstrate the validity of the proposed modeling approach.
  • Keywords
    electromagnetic interference; recurrent neural nets; electromagnetic susceptibility; electronic devices; interference responses; internal circuits; modeling approach; recurrent neural networks; Circuit simulation; Electromagnetic analysis; Electromagnetic interference; Electromagnetic modeling; Frequency domain analysis; Industrial electronics; Medical services; Power system modeling; Recurrent neural networks; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electromagnetic Compatibility, 2009 20th International Zurich Symposium on
  • Conference_Location
    Zurich
  • Print_ISBN
    978-3-9523286-4-4
  • Type

    conf

  • DOI
    10.1109/EMCZUR.2009.4783448
  • Filename
    4783448