• DocumentCode
    2286895
  • Title

    Theoretical considerations on the dynamics of hysteresis binary Hopfield networks for combinatorial optimization

  • Author

    Matsuda, Satoshi

  • Author_Institution
    901-25, Eda-cho, Aoba-ku, Yokohama, Japan
  • Volume
    6
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    480
  • Abstract
    It has been reported that hysteresis binary Hopfield networks achieve good performance for many combinatorial optimization problems. The theoretical analysis of the network dynamics or this good performance, however, is not given yet. In this paper, conditions for the convergence to an energy minimum state, and for the stability of the feasible and infeasible solutions to combinatorial optimization problems are shown in terms of the hysteresis size. Then, a theoretical explanation of the good performance of hysteresis binary Hopfield networks is also given. Simulations illustrate these theoretical conclusions
  • Keywords
    Hopfield neural nets; combinatorial mathematics; hysteresis; optimisation; combinatorial optimization; hysteresis binary Hopfield networks; network dynamics; stability; Convergence; Hysteresis; Neurons; Performance analysis; Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
  • Conference_Location
    Como
  • ISSN
    1098-7576
  • Print_ISBN
    0-7695-0619-4
  • Type

    conf

  • DOI
    10.1109/IJCNN.2000.859441
  • Filename
    859441