• DocumentCode
    1548885
  • Title

    Global stability conditions for delayed CNNs

  • Author

    Cao, Jinde

  • Author_Institution
    Dept. of Appl. Math., Southeast Univ., Nanjing, China
  • Volume
    48
  • Issue
    11
  • fYear
    2001
  • fDate
    11/1/2001 12:00:00 AM
  • Firstpage
    1330
  • Lastpage
    1333
  • Abstract
    Based on the Lyapunov stability theorem as well as some facts about the positive definiteness and inequality of matrices, a new sufficient condition is presented for the existence of a unique equilibrium point and its global asymptotic stability for delayed CNNs. This condition imposes constraints on the feedback matrices independent of the delay parameter. This condition is less restrictive than that given in earlier references
  • Keywords
    Lyapunov methods; asymptotic stability; cellular neural nets; feedback; matrix algebra; DCNNs; Lyapunov stability theorem; cellular neural networks; delay parameter; delayed CNNs; feedback matrices; global asymptotic stability; global stability conditions; matrix inequality; positive definiteness; sufficient condition; unique equilibrium point; Asymptotic stability; Cellular neural networks; Delay effects; Linear matrix inequalities; Lyapunov method; Neural networks; Neurofeedback; Output feedback; State feedback; Sufficient conditions;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7122
  • Type

    jour

  • DOI
    10.1109/81.964422
  • Filename
    964422