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Description
  • Aproximace vysoko dimenzionálních zobrazení pomocí neuronových sítí je studována v kontextu nelineární aproximační teorie. Je ukázáno, že je možné se vyhnout tzv. prokletí dimenzionality pokud jsou určité normy zobrazení nízké. Jsou popsány vlastnosti a metody odhadu těchto norem. Výsledky jsou aplikovány na RBF a perceptronové sítě. (cs)
  • Approximations of high-dimensional mappings by neural network is investigated in the context of nonlinear approximation theory. It is shown that the %22curse of dimensionality%22 can be avoided when certain norms of mappings are kept low. There are described properties and methods of derivation of estimates of such norms. The results are applied to perceptron and RBF networks.
  • Approximations of high-dimensional mappings by neural network is investigated in the context of nonlinear approximation theory. It is shown that the %22curse of dimensionality%22 can be avoided when certain norms of mappings are kept low. There are described properties and methods of derivation of estimates of such norms. The results are applied to perceptron and RBF networks. (en)
Title
  • Mappings between High-Dimensional Representations in Connectionistic Systems
  • Mappings between High-Dimensional Representations in Connectionistic Systems (en)
  • Transformace vysoko dimenzionálních reprezentací v konekcionistických systémech (cs)
skos:prefLabel
  • Mappings between High-Dimensional Representations in Connectionistic Systems
  • Mappings between High-Dimensional Representations in Connectionistic Systems (en)
  • Transformace vysoko dimenzionálních reprezentací v konekcionistických systémech (cs)
skos:notation
  • RIV/67985807:_____/04:00103262!RIV/2005/AV0/A06005/N
http://linked.open.../vavai/riv/strany
  • 31;46
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  • P(GA201/00/1489), Z(AV0Z1030915)
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  • 572307
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  • RIV/67985807:_____/04:00103262
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  • approximations of high-dimensional functions; perceptron networks; variation norm (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [E7D060951987]
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  • Košice
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  • New Jersey
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  • Quo Vadis Machine Intelligence?
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  • Kůrková, Věra
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number of pages
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  • World Scientific
https://schema.org/isbn
  • 981-238-751-X
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