97392 20230622083323.0 doi 10.3390/math8122197 sideral 121777 ART-2020-121777 eng Gonzalez-Diaz, R. Neural-network-based curve fitting using totally positive rational bases 2020 Access copy available to the general public Unrestricted This paper proposes a method for learning the process of curve fitting through a general class of totally positive rational bases. The approximation is achieved by finding suitable weights and control points to fit the given set of data points using a neural network and a training algorithm, called AdaMax algorithm, which is a first-order gradient-based stochastic optimization. The neural network presented in this paper is novel and based on a recent generalization of rational curves which inherit geometric properties and algorithms of the traditional rational Bézier curves. The neural network has been applied to different kinds of datasets and it has been compared with the traditional least-squares method to test its performance. The obtained results show that our method can generate a satisfactory approximation. info:eu-repo/grantAgreement/ES/DGA-FEDER/Construyendo Europa desde Aragón info:eu-repo/grantAgreement/ES/MCIU-AEI/PGC2018-096321-B-I00 info:eu-repo/grantAgreement/ES/MICINN-FEDER/PID2019-107339GB-I00 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 2.258 2020 MATHEMATICS 24 / 330 = 0.073 2020 Q1 T1 0.495 2020 Mathematics (miscellaneous) 2020 Q2 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Mainar, E. Universidad de Zaragoza (orcid)0000-0002-1101-6230 Paluzo-Hidalgo, E. Rubio, B. Universidad de Zaragoza (orcid)0000-0001-9130-0794 2005 595 Universidad de Zaragoza Dpto. Matemática Aplicada Área Matemática Aplicada 8, 12 (2020), 2197 [1-19] Mathematics (Basel) Mathematics 2227-7390 569854 http://zaguan.unizar.es/record/97392/files/texto_completo.pdf Versión publicada 491725 http://zaguan.unizar.es/record/97392/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:97392 articulos driver 2023-06-21-15:03:27 ARTICLE