• DocumentCode
    1424066
  • Title

    Robust stability for interval Hopfield neural networks with time delay

  • Author

    Liao, Xiaofeng ; Yu, Juebang

  • Author_Institution
    Dept. of Optoelectron. Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • Volume
    9
  • Issue
    5
  • fYear
    1998
  • fDate
    9/1/1998 12:00:00 AM
  • Firstpage
    1042
  • Lastpage
    1045
  • Abstract
    The conventional Hopfield neural network with time delay is intervalized to consider the bounded effect of deviation of network parameters and perturbations yielding a novel interval dynamic Hopfield neural network (IDHNN) model. A sufficient condition related to the existence of unique equilibrium point and its robust stability is derived
  • Keywords
    Hopfield neural nets; delays; stability; IDHNN model; interval dynamic Hopfield neural network; network parameter deviation; network perturbations; robust stability; time delay; unique equilibrium point; Artificial neural networks; Delay effects; Delay estimation; Hopfield neural networks; Integrated circuit interconnections; Magnesium compounds; Neural networks; Neurons; Robust stability; Sufficient conditions;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.712187
  • Filename
    712187
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1424066