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A globally convergent method for nonlinear least-squares problems based on the Gauss-Newton model with spectral correction

Journal: Bulletin of Computational Applied Mathematics (Bull CompAMa) (Vol.4, No. 2)

Publication Date:

Authors : ; ;

Page : 7-26

Keywords : Nonlinear least squares; spectral parameter; Gauss-Newton method; global convergence; numerical tests;

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Abstract

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.

Last modified: 2018-08-05 10:10:59