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Description
  • Estimates of network complexity are derived using integral transforms with kernels corresponding to various types of computational units. The results are applied to perceptron networks.
  • Estimates of network complexity are derived using integral transforms with kernels corresponding to various types of computational units. The results are applied to perceptron networks. (en)
Title
  • Model Complexity of Neural Networks and Integral Transforms
  • Model Complexity of Neural Networks and Integral Transforms (en)
skos:prefLabel
  • Model Complexity of Neural Networks and Integral Transforms
  • Model Complexity of Neural Networks and Integral Transforms (en)
skos:notation
  • RIV/67985807:_____/09:00328417!RIV10-AV0-67985807
http://linked.open...avai/riv/aktivita
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  • P(GA201/08/1744), Z(AV0Z10300504)
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  • 326650
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  • RIV/67985807:_____/09:00328417
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  • model complexity; integral transforms induced by computational units (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [2FD6E9883D8E]
http://linked.open...v/mistoKonaniAkce
  • Limassol
http://linked.open...i/riv/mistoVydani
  • Berlin
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  • Artificial Neural Networks - ICANN 2009
http://linked.open...in/vavai/riv/obor
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  • Kůrková, Věra
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  • 000275896600073
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number of pages
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  • Springer-Verlag
https://schema.org/isbn
  • 978-3-642-04273-7
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