Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/98269
Type: Artigo de periódico
Title: An Algorithm For Solving Sparse Nonlinear Least Squares Problems
Author: Martinez J.M.
Abstract: We introduce a new method for solving Nonlinear Least Squares problems when the Jacobian matrix of the system is large and sparse. The main features of the new method are the following: a) The Gauss-Newton equation is "partially" solved at each iteration using a preconditioned Conjugate Gradient algorithm. b) The new point is obtained using a two-dimensional trust region scheme, similar to the one introduced by Bulteau and Vial. We prove global and local convergence results and we present some numerical experiments. © 1987 Springer-Verlag.
Editor: Springer-Verlag
Rights: fechado
Identifier DOI: 10.1007/BF02239974
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0023568876&partnerID=40&md5=da045e96099a936e3ce0b0816cfa0b3b
Date Issue: 1987
Appears in Collections:Unicamp - Artigos e Outros Documentos

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