A finite-size scaling investigation for Q-state Hopfield models: Storage capacity and basins of attraction

T. Stiefvater, K. R. Muller

    Research output: Contribution to journalArticlepeer-review

    5 Citations (Scopus)

    Abstract

    The storage capacity of a Q-state Hopfield network is determined via finite-size scaling for parallel dynamics and Q<or=8. The results are in good agreement with theoretical predictions by Rieger. The basins of attraction and other associative memory properties are discussed for Q=4, 6. A self-controlling Q-state model with improved basins of attraction is proposed.

    Original languageEnglish
    Article number019
    Pages (from-to)5919-5929
    Number of pages11
    JournalJournal of Physics A: Mathematical and General
    Volume25
    Issue number22
    DOIs
    Publication statusPublished - 1992

    ASJC Scopus subject areas

    • Statistical and Nonlinear Physics
    • Mathematical Physics
    • General Physics and Astronomy

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