Estimates of Network Complexity and Integral Representations
Result description
Upper bounds on rates of approximation by neural networks are derived for functions representable as integrals in the form of networks with infinitely many units. The bounds are applied to perceptron networks.
Keywords
rates of approximation by neural networksintegral representationsBochner integral
The result's identifiers
Result code in IS VaVaI
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Estimates of Network Complexity and Integral Representations
Original language description
Upper bounds on rates of approximation by neural networks are derived for functions representable as integrals in the form of networks with infinitely many units. The bounds are applied to perceptron networks.
Czech name
Odhady složitosti sítí a integrální reprezentace
Czech description
Horní odhady rychlosti aproximace neuronovými sítěmi jsou odvozeny pro funkce, které lze reprezentovat jako integrály ve tvaru neuronových sítí s nekonečně mnoha jednotkami. Odhady jsou aplikovány na perceptronové síte.
Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Neural Networks - ICANN 2008
ISBN
978-3-540-87535-2
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
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Publisher name
Springer
Place of publication
Berlin
Event location
Prague
Event date
Sep 3, 2008
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000259566200004
Basic information
Result type
D - Article in proceedings
CEP
IN - Informatics
Year of implementation
2008