On the problem of neural network decomposition into some subnets

dc.creatorLitinskii, Leonid B.
dc.date2000-01-18
dc.date.accessioned2026-07-07T02:36:35Z
dc.date.available2026-07-07T02:36:35Z
dc.descriptionAn artificial neural network is usually treated as a whole system, being characterized by its ground state (the global minimum of the energy functional), the set of fixed points, their basins of attraction, etc. However, it is quite natural to suppose that a large network may consist of a set of almost autonome subnets. Each subnet works independently (or almost independently) and analyzes the same pattern from other points of view. It seems that it is a proper model for the natural neural networks. We discuss the problem of decomposition of a neural network into a set of weakly coupled subnets. The used technique is similar to the method for {\it the extremal grouping of parameters}, proposed by E.M.Braverman (1970).
dc.descriptionOne old paper, 10 pages
dc.identifierhttps://arxiv.org/abs/cond-mat/0001247
dc.identifierhttp://arxiv.org/abs/cond-mat/0001247
dc.identifierMathematical Modelling (1996), v.8, pp. 119-127 (in russian)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/15971
dc.subjectDisordered Systems and Neural Networks
dc.titleOn the problem of neural network decomposition into some subnets
dc.typetext

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