• DocumentCode
    3072592
  • Title

    Frequency domain robustness analysis of Hopfield and modified Hopfield neural networks

  • Author

    Shen, Jie ; Balakrishnan, S.N.

  • Author_Institution
    Dept. of Mech. & Aerosp. Eng., Missouri Univ., Rolla, MO, USA
  • Volume
    6
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    4183
  • Abstract
    A variant of Hopfield neural network, called the modified Hopfield network, is formulated in this study. This class of networks consists of parallel recurrent networks which have variable dimensions that can be changed to fit the problem under consideration. It has a structure to implement an inverse transformation that is essential for embedding optimal control gain sequences. Equilibrium solutions of this network are discussed. The robustness of this network and the classical Hopfield network are carried out in the frequency domain using describing functions
  • Keywords
    Hopfield neural nets; circuit stability; frequency-domain analysis; inverse problems; optimal control; transforms; Hopfield neural networks; frequency domain analysis; inverse transformation; optimal control; recurrent networks; robustness; stability; Aerospace engineering; Artificial neural networks; Control systems; Frequency domain analysis; Hopfield neural networks; Neural networks; Neurons; Optimal control; Robust stability; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 1999. Proceedings of the 1999
  • Conference_Location
    San Diego, CA
  • ISSN
    0743-1619
  • Print_ISBN
    0-7803-4990-3
  • Type

    conf

  • DOI
    10.1109/ACC.1999.786345
  • Filename
    786345