Jana Stanclová

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Associative memories represent a model of artificial neural networks applicable to the information storage and retrieval. However, the performance of traditional associative memories is very sensitive to the number of stored patterns and their mutual similarities. In order to avoid limitations imposed by processing larger amounts of mutually correlated(More)
Title: Hierarchical associative memories Author: RNDr. Jana Štanclová email: stanclova@ksi.ms.mff.cuni.cz phone: +420 2 2191 4260 Department: Department of Software Engineering Faculty of Mathematics and Physics Charles University in Prague, Czech Republic Advisor: RNDr. Iveta Mrázová, CSc. email: mrazova@ksi.ms.mff.cuni.cz phone: +420 2 2191 4219 Mailing(More)
  • Univerzita Karlova, Praze, +7 authors Ondřejčepek
  • 2005
Completeness of resolution (Quine’s theorem) claims, that given an arbitrary CNF representation F of a Boolean function f , every prime implicate of f can be derived from F by a chain of resolutions. However, Quine’s theorem gives no bound on the degrees of intermediate resolvents, which in turns means that the length of the derivation chain may be(More)
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