Local analysis of a spectral correction for the Gauss-Newton model applied to quadratic residual problems

DOI10.1007/s11075-016-0101-3zbMath1357.90152OpenAlexW2298107905MaRDI QIDQ329315

Douglas S. Gonçalves, Sandra Augusta Santos

Publication date: 21 October 2016

Published in: Numerical Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11075-016-0101-3

zbMATH Keywords

spectral parameterlocal convergenceGauss-Newton methodnonlinear least squaresquadratic residues

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Numerical methods based on nonlinear programming (49M37)

Related Items

A globally convergent method for nonlinear least-squares problems based on the Gauss-Newton model with spectral correction ⋮ 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 ⋮ A structured quasi-Newton algorithm with nonmonotone search strategy for structured NLS problems and its application in robotic motion control ⋮ Structured diagonal Gauss-Newton method for nonlinear least squares

Uses Software

• levmar
• Filtrane

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• On the local convergence of a derivative-free algorithm for least-squares minimization
• Recent advances in numerical methods for nonlinear equations and nonlinear least squares
• Local convergence analysis of the Gauss-Newton method under a majorant condition
• Levenberg--Marquardt methods with strong local convergence properties for solving nonlinear equations with convex constraints
• A unified local convergence analysis of inexact constrained Levenberg-Marquardt methods
• Convergence analysis of a proximal Gauss-Newton method
• Derivative free analogues of the Levenberg-Marquardt and Gauss algorithms for nonlinear least squares approximation
• Convergence of the Gauss--Newton Method for Convex Composite Optimization under a Majorant Condition
• Convergence of a Regularized Euclidean Residual Algorithm for Nonlinear Least-Squares
• A Derivative-Free Algorithm for Least-Squares Minimization
• Hessian Matrix vs. Gauss–Newton Hessian Matrix
• The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem
• Two-Point Step Size Gradient Methods
• An Algorithm for Least-Squares Estimation of Nonlinear Parameters
• Specialised versus general-purpose algorithms for minimising functions that are sums of squared terms
• The estimation of the hessian matrix in nonlinear least squares problems with non-zero residuals
• Algorithms for the Solution of the Nonlinear Least-Squares Problem
• Numerical Optimization
• Nonmonotone Spectral Projected Gradient Methods on Convex Sets
• Strong local convergence properties of adaptive regularized methods for nonlinear least squares
• Modified Gauss–Newton scheme with worst case guarantees for global performance
• Approximate Gauss–Newton Methods for Nonlinear Least Squares Problems
• An Improved Marquardt Procedure for Nonlinear Regressions
• A method for the solution of certain non-linear problems in least squares