• DocumentCode
    395499
  • Title

    Exponential stability of the steady state solution of Hopfield neural networks with reaction-diffusion terms under the L2 norm

  • Author

    Zhao, Xinquan ; Zhou, Lun ; Liao, Xiaoxin

  • Author_Institution
    Dept. of Autom. Control Eng., Huazhong Univ. of Sci. & Technol., Hubei, China
  • Volume
    3
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    1114
  • Abstract
    In this paper, local asymptotic stability and global asymptotic stability of the steady state solutions of Hopfield neural networks with reaction-diffusion terms are investigated. Under the L2 norm, applying the differential inequality some sufficiency criterions for local exponential stability and global exponential stability of the steady state solution of system are established.
  • Keywords
    Hopfield neural nets; asymptotic stability; circuit stability; Hopfield neural networks; exponential stability; global asymptotic stability; reaction-diffusion terms; steady state solution; Asymptotic stability; Educational institutions; Equations; Hopfield neural networks; Intelligent networks; Lyapunov method; Neural networks; Roads; Stability criteria; Steady-state;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1202795
  • Filename
    1202795
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=395499