Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/54469

TítuloA numerical optimization approach to generate smoothing spherical splines
Autor(es)Machado, L.
Monteiro, M. Teresa T.
Palavras-chaveGeodesics
Geometric smoothing splines
Least squares
Nonlinear constrained optimization
Data2017
EditoraElsevier Science BV
RevistaJournal of Geometry and Physics
Resumo(s)Approximating data in curved spaces is a common procedure that is extremely required by modern applications arising, for instance, in aerospace and robotics industries.Here, we are particularly interested in finding smoothing cubic splines that best fit given data in the Euclidean sphere. To achieve this aim, a least squares optimization problem based on the minimization of a certain cost functional is formulated. To solve the problem a numerical algorithm is implemented using several routines from MATLAB toolboxes. The proposed algorithm is shown to be easy to implement, very accurate and precise for spherical data chosen randomly. (C) 2016 Elsevier B.V. All rights reserved.
TipoArtigo
URIhttps://hdl.handle.net/1822/54469
DOI10.1016/j.geomphys.2016.10.007
ISSN0393-0440
Arbitragem científicayes
AcessoAcesso restrito UMinho
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals

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