Informatica logo


Login Register

  1. Home
  2. Issues
  3. Volume 21, Issue 3 (2010)
  4. An Expansion of the Neural Network Theor ...

Informatica

Information Submit your article For Referees Help ATTENTION!
  • Article info
  • Related articles
  • More
    Article info Related articles

An Expansion of the Neural Network Theory by Introducing Hebb Postulate
Volume 21, Issue 3 (2010), pp. 339–348
Algis Garliauskas  

Authors

 
Placeholder
https://doi.org/10.15388/Informatica.2010.292
Pub. online: 1 January 2010      Type: Research Article     

Received
1 June 2009
Accepted
1 April 2010
Published
1 January 2010

Abstract

In the presented paper, some issues of the fundamental classical mechanics theory in the sense of Ising physics are introduced into the applied neural network area. The expansion of the neural networks theory is based primarily on introducing Hebb postulate into the mean field theory as an instrument of analysis of complex systems. Appropriate propositions and a theorem with proofs were proposed. In addition, some computational background is presented and discussed.

Related articles PDF XML
Related articles PDF XML

Copyright
No copyright data available.

Keywords
Hamiltonian Ising model Hebb postulate neural network memory capacity

Metrics
since January 2020
770

Article info
views

0

Full article
views

512

PDF
downloads

194

XML
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

INFORMATICA

  • Online ISSN: 1822-8844
  • Print ISSN: 0868-4952
  • Copyright © 2023 Vilnius University

About

  • About journal

For contributors

  • OA Policy
  • Submit your article
  • Instructions for Referees
    •  

    •  

Contact us

  • Institute of Data Science and Digital Technologies
  • Vilnius University

    Akademijos St. 4

    08412 Vilnius, Lithuania

    Phone: (+370 5) 2109 338

    E-mail: informatica@mii.vu.lt

    https://informatica.vu.lt/journal/INFORMATICA
Powered by PubliMill  •  Privacy policy