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|Type:||Artigo de periódico|
|Title:||An Algorithm For Solving Sparse Nonlinear Least Squares Problems|
|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.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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