• DocumentCode
    2748862
  • Title

    Estimate of the number of equilibria in continuous-time Hopfield neural networks

  • Author

    Yujian, Li

  • Author_Institution
    Intelligence Res. Center, Beijing Univ. of Posts & Telecommun., China
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1606
  • Abstract
    A new method is developed to estimate the number of equilibria in continuous-time Hopfield (1982, 1984) neural dynamic systems. By this new method, the number of equilibria in (S) is described clearly when the connection matrix T is upper trigonal, namely, Tij=0 (i>j). Furthermore, it is reasonably conjectured that if T is an arbitrary real matrix, the total number of equilibria in (GS) is no greater than 3a and the total number of asymptotically stable equilibria in (GS) is no greater than 2"
  • Keywords
    Hopfield neural nets; continuous time systems; matrix algebra; parameter estimation; arbitrary real matrix; asymptotically stable equilibria; continuous-time Hopfield neural dynamic systems; continuous-time Hopfield neural networks; equilibria number estimation; upper triagonal connection matrix; Differential equations; Hopfield neural networks; Intelligent networks; Stability analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-5747-7
  • Type

    conf

  • DOI
    10.1109/ICOSP.2000.893408
  • Filename
    893408
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2748862