Collective properties of a system of mutually learning neuronal nets in the information field

A. Yu Grosberg, N. V. Khrustova

    Research output: Contribution to journalArticlepeer-review

    Abstract

    A model of a system of neuronal nets interacting in informational form with each other through transmission and associative recognition of signals is studied by computer modelling. Two qualitatively different regimes are found in the system as a function of the size of the parameter of learning determining the weight of the entry into the memory of each neuronal net of each incoming signal: the chaotic alternation of images almost independent of the initial one and collective recognition of the initial image when to it is compared associatively a certain limiting cycle of images. The similarity of the model to the Eigen hypercycle is established and discussed.

    Original languageEnglish (US)
    Pages (from-to)751-759
    Number of pages9
    JournalBiophysics
    Volume38
    Issue number4
    StatePublished - 1993

    ASJC Scopus subject areas

    • Biophysics

    Fingerprint Dive into the research topics of 'Collective properties of a system of mutually learning neuronal nets in the information field'. Together they form a unique fingerprint.

    Cite this