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Exponential Transients in Continuous-Time Symmetric Hopfield Nets.

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F01%3A06010035" target="_blank" >RIV/67985807:_____/01:06010035 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Exponential Transients in Continuous-Time Symmetric Hopfield Nets.

  • Original language description

    We establish a fundamental result in the theory of continuosu-time neural computation, by showing that so called continuous-time symmetric Hopfield nets, whose asymptotic convergence is always guaranteed by the existence of a Liapunov function may, in the worst case, possess a transient period that is exponential in the network size. The result stands in contrast to e.g. the use of such network models in combinatorial optimization applications.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BA - General mathematics

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2001

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Artificial Neural Networks - ICANN 2001. Proceedings.

  • ISBN

    3-540-42486-5

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    806-813

  • Publisher name

    Springer-Verlag

  • Place of publication

    Berlin

  • Event location

    Vienna [AT]

  • Event date

    Aug 21, 2001

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article