• DocumentCode
    1146423
  • Title

    Global robust stability of delayed neural networks

  • Author

    Arik, Sabri

  • Author_Institution
    Dept. of Electr.-Electron. Eng., Istanbul Univ., Turkey
  • Volume
    50
  • Issue
    1
  • fYear
    2003
  • Firstpage
    156
  • Lastpage
    160
  • Abstract
    This work presents a sufficient condition for the existence, uniqueness, and global robust stability of the equilibrium point for Hopfield-type delayed neural networks. The result imposes constraint conditions on the boundary values of the network parameters independently of the delay parameter. This result is compared with the previous results derived in the literature.
  • Keywords
    Hopfield neural nets; delays; network parameters; stability; Hopfield-type neural networks; boundary values; constraint conditions; delay parameter; delayed neural networks; equilibrium analysis; equilibrium point; global robust stability; network parameters; Asymptotic stability; Delay effects; Equations; Hopfield neural networks; Neural networks; Neurons; Robust stability; Stability analysis; Sufficient conditions; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7122
  • Type

    jour

  • DOI
    10.1109/TCSI.2002.807515
  • Filename
    1179162
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1146423