Jacobian-free implicit inner-iteration preconditioner for nonlinear least squares problems

DOI10.1007/s10915-016-0167-zzbMath1352.65158OpenAlexW2270206726MaRDI QIDQ333209

Ning Zheng, Ken Hayami, Wei Xu

Publication date: 28 October 2016

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10915-016-0167-z

zbMATH Keywords

convergencepreconditioningautomatic differentiationNewton methodnumerical experimenttrust region methodBA-GMRES methodCGLS methoddogleg methodnonlinear least squares problemweighted Jacobi method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Quadratic programming (90C20) Methods of quasi-Newton type (90C53) Interior-point methods (90C51) Numerical differentiation (65D25) Preconditioners for iterative methods (65F08)

Related Items (5)

The adjoint Petrov-Galerkin method for non-linear model reduction ⋮ Structured two-point stepsize gradient methods for nonlinear least squares ⋮ Structured adaptive spectral-based algorithms for nonlinear least squares problems with robotic arm modelling applications ⋮ A structured diagonal Hessian approximation method with evaluation complexity analysis for nonlinear least squares ⋮ A brief survey of methods for solving nonlinear least-squares problems

Uses Software

• Matlab
• ADMAT
• tn

Cites Work

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