• DocumentCode
    302534
  • Title

    Absolute stability of nonsymmetric neural networks

  • Author

    Arik, Sabri ; Tavsanoglu, Vedat

  • Author_Institution
    Centre for Res. in Inf. Eng., South Bank Univ., London, UK
  • Volume
    3
  • fYear
    1996
  • fDate
    12-15 May 1996
  • Firstpage
    441
  • Abstract
    In this paper, two conditions concerning absolute stability of nonsymmetric dynamical neural networks are presented. Each condition guarantees the uniqueness and global asymptotic stability of the equilibrium point for different classes of activation functions and under different constraint conditions imposed on the interconnection matrix
  • Keywords
    absolute stability; asymptotic stability; neural nets; absolute stability; activation functions; constraint conditions; equilibrium point; global asymptotic stability; interconnection matrix; nonsymmetric dynamical neural networks; uniqueness; Asymptotic stability; Equations; Lyapunov method; Neural networks; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    0-7803-3073-0
  • Type

    conf

  • DOI
    10.1109/ISCAS.1996.541628
  • Filename
    541628
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=302534