• DocumentCode
    2496689
  • Title

    Investigation of generalized Hopfield model by statistical physics methods

  • Author

    Kryzhanovsky, Boris V. ; Litinskii, Leonid B.

  • Author_Institution
    Center of Opt. Neural Technol., Russian Acad. of Sci., Moscow, Russia
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The proposed generalization of the Hopfield model consists in assigning different weight coefficients to input patterns that are used to construct the Hebb connection matrix. Application of statistical physics methods to such a system gives unexpected results even for the simplest variant of differences of weight coefficients. Namely, there are unusual behaviors of the critical value of the load parameter and of the overlap of the state with the pattern.
  • Keywords
    Hopfield neural nets; generalisation (artificial intelligence); matrix algebra; statistical analysis; Hebb connection matrix; generalized Hopfield model; statistical physics methods; Analytical models; Associative memory; Character recognition; Equations; Mathematical model; Physics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2010 International Joint Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-6916-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2010.5596872
  • Filename
    5596872