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An Adaptable Boolean Neural Net Obtained by Connecting Seven Node Asssemblies

  • F. E. Lauria
  • R. Prevete
  • M. Milo
  • S. Visco
Conference paper
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)

Abstract

We present the seven node Boolean neural subnet playing the assembly role so allowing us to implement an Hebbian rule in the Boolean net obtained by connecting them.

Keywords

Sensory Input Coupling Coefficient Empty Circle Hebbian Rule Node Assembly 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Lauria, F. E., M. Sette, S. Visco — Adaptable Boolean neural networks-Fridericiana Scientia, Liguori (Napoli) (1997) 212. ISBN 88-207-2676-9. http://www.na.infn.it/Gener/cyber/nnet.htm Google Scholar
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    Rumelhart, D. E., J. L. McClelland and the PDP Research Group — Parallel distributed processing. Vol I Foundations-MIT Press, Cambridge (Mass.) USA (1986) 547 + xx.Google Scholar
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    Caianiello, E. R. — Outline of a theory of thought processes and thinking machines-J. Theor. Biol. 2 (1961) 204–235.MathSciNetCrossRefGoogle Scholar
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    Lauria F. E., M. Sette — “Teaching macros through program execution examples” E. R. Caianiello ed. “Neural nets WIRN Vietri-92” World Sc. (Singapore), (1992) 204–209.Google Scholar

Copyright information

© Springer-Verlag London Limited 1999

Authors and Affiliations

  • F. E. Lauria
    • 1
  • R. Prevete
    • 1
  • M. Milo
    • 1
  • S. Visco
    • 1
  1. 1.Dipartimento di Scienze Fisiche dell’ Università di Napoli & Istituto Nazionale di Fisica della MateriaMostra D’ OltremareNaplesItaly (EU)

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