• DocumentCode
    3251390
  • Title

    Dynamical stability and parameter selection in neural optimization

  • Author

    Kamgar-Parsi, B. ; Kamgar-Parsi, B.

  • Author_Institution
    US Naval Res. Lab., Washington, DC, USA
  • Volume
    4
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    566
  • Abstract
    Finding suitable parameter values in solving optimization problems with the Hopfield net is of crucial importance. The authors present a systematic approach, based on analyzing dynamical stability of valid solutions for finding relationships among the parameters which make their selection much easier. This technique can show whether the problem formulation is flawed. As an example they discuss the Hopfield-Tank formulation of the traveling salesman problem and show that it is dynamically unstable, hence obtaining valid solutions is difficult. The modified formulation given by S.Y.B. Aiyer et al. (1990) which overcomes the instability problems is also discussed
  • Keywords
    Hopfield neural nets; optimisation; Hopfield-Tank formulation; dynamical stability; neural optimization; parameter selection; traveling salesman problem; valid solutions; Cost function; Differential equations; Government; Hopfield neural networks; Laboratories; Neural networks; Neurons; Protection; Stability analysis; Traveling salesman problems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1992. IJCNN., International Joint Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-0559-0
  • Type

    conf

  • DOI
    10.1109/IJCNN.1992.227259
  • Filename
    227259