Classification of the finite algebra concepts for the description of neural network elements
Authors:
About authors
- Ph.D., Dr.Sci. professor National Mineral Resources University (Mining University)
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.
Funding:
None
References
- Gorbatov V.A. The fundamentals of discrete mathematics. Information mathematics. Moscow, 2000. 544 p.
- Ezhov A.A., Shumskiy S.A. Neurocomputing and its use in economics and commerce. URL: http:/www.intuit.ru/
- Mutter V.M., Trofimov V.V., Ivanova I.V., Kalinushkina M.Y. Mathematical basics of digital equipment. Saint Petersburg, 1999. 351 p.
- URL: http://ru.wikipedia.org/wiki
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