Truncated gauss-newton algorithms for ILL-conditioned nonlinear least squares problems

Optimization Methods and Software

Volumn 19, Issue 6, 2004, Pages 721-737

  Eriksson, Jerry ^a   Wedin, Per Åke ^a  

^a UMEÅ UNIVERSITY   (Sweden)

Author keywords

III conditioning; Merit functions; Minimum norm Gauss Newton; Nonlinear minimum norm solution; Rank deficiency; Truncated Gauss Newton

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; ITERATIVE METHODS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL OPERATORS; PROBLEM SOLVING;

ILL-CONDITIONING; MERIT FUNCTIONS; MINIMUM-NORM GAUSS-NEWTON; NONLINEAR MINIMUM-NORM SOLUTION; RANK-DEFICIENCY; TRUNCATED GAUSS-NEWTON;

ALGORITHMS;

EID: 10044265544     PISSN: 10556788     EISSN: None     Source Type: Journal    
DOI: 10.1080/10556780410001722471     Document Type: Article

References (4)

1. J. Eriksson (1996). Optimization and regularization of nonlinear least squares problems. PhD thesis, Ume̊ University, Umeå, Sweden.
2. J.E. Dennis and R.B. Schnabel (1983). Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Prentice Hall, Englewood Cliffs, NJ.
3. P. Lindström and P.-Å. Wedin (1988). Methods and software for nonlinear least squares problems. Technical Report UMINF-133.87, Inst. of Information Processing. University of Umeå, Umeå, Sweden.
4. M. Gulliksson, I. Söderkvist, and P.-Å. Wedin (1997). Algorithms for weighted and constrained nonlinear least squares. SIAM Journal of Optimization, 7(1), 208-224.