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Vol 208
Pages:
222-231
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RUS
Article

Classification of the finite algebra concepts for the description of neural network elements

Authors:
I. V. Ivanova
About authors
  • Ph.D., Dr.Sci. professor National Mineral Resources University (Mining University)
Date submitted:
2013-08-27
Date accepted:
2013-10-21
Date published:
2014-07-15

Abstract

Contemporary information systems are characterized not only by the large volume of data stored, but also by its complexity. This complexity manifests in various interconnections this data holds. Thus, complex data is presented as a set of some basic items and a body of connections linking the data items. Complex information systems are formalized with the concepts of graph, mograph and, lately, neural network. Classification of the finite algebra concepts, such as correspondence and relation (ternary or binary), is examined. Specific kinds of relations and their properties are intended to use for the description of neural network elements.

Keywords:
classification of relation neural network elements
Funding:

None

Go to volume 208

References

  1. Gorbatov V.A. The fundamentals of discrete mathematics. Information mathematics. Moscow, 2000. 544 p.
  2. Ezhov A.A., Shumskiy S.A. Neurocomputing and its use in economics and commerce. URL: http:/www.intuit.ru/
  3. Mutter V.M., Trofimov V.V., Ivanova I.V., Kalinushkina M.Y. Mathematical basics of digital equipment. Saint Petersburg, 1999. 351 p.
  4. URL: http://ru.wikipedia.org/wiki

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