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A new domain decomposition for B-spline Neural Networks

dc.contributor.authorCabrita, Cristiano Lourenço
dc.contributor.authorRuano, Antonio
dc.contributor.authorKóczy, László T.
dc.date.accessioned2013-01-29T14:35:38Z
dc.date.available2013-01-29T14:35:38Z
dc.date.issued2010
dc.date.updated2013-01-26T16:42:14Z
dc.description.abstractB-spline Neural Networks (BSNNs) belong to the class of networks termed grid or lattice-based associative memories networks (AMN). The grid is a key feature since it allows these networks to exhibit relevant properties which make them efficient in solving problems namely, functional approximation, non-linear system identification, and on-line control. The main problem associated with BSNNs is that the model complexity grows exponentially with the number of input variables. To tackle this drawback, different authors developed heuristics for functional decomposition, such as the ASMOD algorithm or evolutionary approaches [2]. In this paper, we present a complementary approach, by allowing the properties of B-spline models to be achieved by non-full grids. This approach can be applied either to a single model or to an ASMOD decomposition. Simulation results show that comparable results, in terms of approximations can be obtained with less complex models.por
dc.identifier.citationCabrita, Cristiano L.; Ruano, Antonio E. B.; Koczy, Laszlo T. A new domain decomposition for B-spline Neural Networks, Trabalho apresentado em 2010 International Joint Conference on Neural Networks (IJCNN), In Proceedings of the 2010 International Joint Conference on Neural Networks (IJCNN), Barcelona, Spain, 2010.por
dc.identifier.isbn978-1-4244-6916-1
dc.identifier.otherAUT: CCA01443; ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2135
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherIEEEpor
dc.titleA new domain decomposition for B-spline Neural Networkspor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceBarcelona, Spainpor
oaire.citation.endPage8por
oaire.citation.startPage1por
oaire.citation.title2010 International Joint Conference on Neural Networks (IJCNN)por
person.familyNameCabrita
person.familyNameRuano
person.givenNameCristiano Lourenço
person.givenNameAntonio
person.identifier.ciencia-idFF1E-13A0-A269
person.identifier.orcid0000-0003-4946-0465
person.identifier.orcid0000-0002-6308-8666
person.identifier.ridB-4135-2008
person.identifier.scopus-author-id55958626100
person.identifier.scopus-author-id7004284159
rcaap.rightsrestrictedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication081b091f-c9fa-470a-9a28-51fe4c85864a
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery13813664-b68b-40aa-97a9-91481a31ebf2

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