eprintid: 1696
rev_number: 8
eprint_status: archive
userid: 46
dir: disk0/00/00/16/96
datestamp: 2013-09-12 11:06:41
lastmod: 2013-09-16 12:03:00
status_changed: 2013-09-12 11:06:41
type: book_section
metadata_visibility: show
creators_name: Gnecco, Giorgio
creators_name: Kůrková, Věra
creators_name: Sanguineti, Marcello
creators_id: giorgio.gnecco@imtlucca.it
creators_id: 
creators_id: 
title: Bounds for Approximate Solutions of Fredholm Integral Equations Using Kernel Networks
ispublished: pub
subjects: QA75
divisions: CSA
full_text_status: none
keywords: Radial and kernel networks; approximation of solutions of integral equations by kernel networks; model complexity
note: Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN 2011)held in Espoo, Finland, June 14th-17th, 2011
abstract: Approximation of solutions of integral equations by networks with kernel units is investigated theoretically. There are derived upper bounds on speed of decrease of errors in approximation of solutions of Fredholm integral equations by kernel networks with increasing numbers of units. The estimates are obtained for Gaussian and degenerate kernels.
date: 2011
date_type: published
series: Lecture Notes in Computer Science
number: 6791
publisher: Springer
pagerange: 126-133
id_number: 10.1007/978-3-642-21735-7_16
refereed: TRUE
isbn: 978-3-642-21734-0
book_title: Artificial Neural Networks and Machine Learning – ICANN 2011
official_url: http://dx.doi.org/10.1007/978-3-642-21735-7_16
citation:   Gnecco, Giorgio and Kůrková, Věra and Sanguineti, Marcello  Bounds for Approximate Solutions of Fredholm Integral Equations Using Kernel Networks.   In:  Artificial Neural Networks and Machine Learning – ICANN 2011.   Lecture Notes in Computer Science  (6791).  Springer, pp. 126-133.  ISBN 978-3-642-21734-0      (2011)