Mesh Independence for Nonlinear Least Squares Problems with Norm Constraints

DOI10.1137/0803005zbMath0771.65030OpenAlexW2055631011WikidataQ58048168 ScholiaQ58048168MaRDI QIDQ4697310

Matthias Heinkenschloss

Publication date: 29 June 1993

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1911/101683

zbMATH Keywords

convergencenumerical exampleparameter identificationHilbert spacesnonlinear least squares problemsGauss-Newton methodmesh independence

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Programming in abstract spaces (90C48) Numerical solutions to equations with nonlinear operators (65J15) Mesh generation, refinement, and adaptive methods for ordinary differential equations (65L50)

Related Items (12)

On the solution of a two ball trust region subproblem ⋮ Learning physics-based models from data: perspectives from inverse problems and model reduction ⋮ Generalized proximal-type methods for weak vector variational inequality problems in Banach spaces ⋮ Coupling vs decoupling approaches for PDE/ODE systems modeling intercellular signaling ⋮ A trust-region strategy for minimization on arbitrary domains ⋮ Mesh-Independence of Lagrange-SQP Methods with Lipschitz-Continuous Lagrange Multiplier Updates ⋮ An adaptive regularization method in Banach spaces ⋮ Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs ⋮ trlib: a vector-free implementation of the GLTR method for iterative solution of the trust region problem ⋮ Approximate generalized proximal-type method for convex vector optimization problem in Banach spaces ⋮ Quadratic optimization with two ball constraints ⋮ Functionally graded materials for prescribed field evolution

This page was built for publication: Mesh Independence for Nonlinear Least Squares Problems with Norm Constraints