Preconditioning and globalizing conjugate gradients in dual space for quadratically penalized nonlinear-least squares problems

Computational Optimization and Applications

Volumn 54, Issue 1, 2013, Pages 1-25

  Gratton, Serge ^a   Gürol, Selime ^b   Toint, Philippe L ^c  

^a UNIVERSITÉ DE TOULOUSE   (France)

^b CERFACS   (France)

^c University of Namur   (Belgium)

Author keywords

Conjugate gradient methods; Data assimilation; Dual space minimization; Globalization; Preconditioning; Trust region methods

Indexed keywords

COMPUTATIONAL COSTS; CONJUGATE GRADIENT; CONVERGENCE BOUNDS; DATA ASSIMILATION; DUAL ALGORITHM; DUAL SPACES; DUALITY PROPERTIES; EXACT ARITHMETIC; GAUSS-NEWTON ALGORITHM; GLOBALIZATION; INVERSE CALCULATION; LEAST SQUARE; LINEAR EQUALITY CONSTRAINTS; MEMORY USAGE; NONLINEAR LEAST SQUARES; PRACTICAL SOLUTIONS; PRECONDITIONING; PRECONDITIONING TECHNIQUES; QUADRATIC MINIMIZATION; SOLUTION METHODS; STANDARD ALGORITHMS; STATISTICAL ANALYSIS SYSTEMS; STOPPING RULE; TRUST REGION; TRUST-REGION METHODS;

ALGORITHMS; CONJUGATE GRADIENT METHOD; LEAST SQUARES APPROXIMATIONS;

ITERATIVE METHODS;

EID: 84871634545     PISSN: 09266003     EISSN: 15732894     Source Type: Journal    
DOI: 10.1007/s10589-012-9478-7     Document Type: Article

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