• DocumentCode
    1838398
  • Title

    Generalized maximum-flow solution based on CNN circuit analysis

  • Author

    Sato, M. ; Tanaka, M.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Sophia Univ., Tokyo, Japan
  • fYear
    2010
  • fDate
    3-5 Feb. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In our previous research, the Maximum-Flow Neural Network (MF-NN) was proposed, and we showed that the MF-NN is possible to solve any maximum-flow problems. However, the MF-NN has problems of convergence of sigmoidal function. In this research, we propose novel MF-NN using piecewise linear function for improving those problems. Moreover, this novel method is possible to considerably reduce a calculation cost.
  • Keywords
    cellular neural nets; network analysis; piecewise linear techniques; CNN circuit analysis; maximum-flow neural network; maximum-flow solution; piecewise linear function; sigmoidal function; Cellular networks; Cellular neural networks; Circuit analysis; Communication networks; Convergence; Neural networks; Parallel processing; Piecewise linear approximation; Piecewise linear techniques; Transportation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Nanoscale Networks and Their Applications (CNNA), 2010 12th International Workshop on
  • Conference_Location
    Berkeley, CA
  • Print_ISBN
    978-1-4244-6679-5
  • Type

    conf

  • DOI
    10.1109/CNNA.2010.5430325
  • Filename
    5430325