Artículos de revistas
A Globally Convergent Method For Nonlinear Least-squares Problems Based On The Gauss-newton Model With Spectral Correction
Registro en:
Bulletin Of Computational Applied Mathematics. Univ Simon Bolivar, v. 4, p. 7 - 26, 2016.
2244-8659
WOS:000390044700002
Autor
Goncalves
Douglas S.; Santos
Sandra A.
Institución
Resumen
This work addresses a spectral correction for the Gauss-Newton model in the solution of nonlinear least-squares problems within a globally convergent algorithmic framework. The nonmonotone line search of Zhang and Hager is the chosen globalization tool. We show that the search directions obtained from the corrected Gauss-Newton model satisfy the conditions that ensure the global convergence under such a line search scheme. A numerical study assesses the impact of using the spectral correction for solving two sets of test problems from the literature. 4 2 7 26