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
  • Physics and Astronomy(all)

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