Nonlinear conjugate gradient methods with structured secant condition for nonlinear least squares problems

DOI10.1016/j.cam.2009.12.031zbMath1223.65043OpenAlexW2084371857MaRDI QIDQ964960

Yasushi Narushima, Hiroshi Yabe, Michiya Kobayashi

Publication date: 21 April 2010

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2009.12.031

zbMATH Keywords

global convergenceconjugate gradient methodleast squares problemsline searchstructured secant condition

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05)

Related Items

Application of a combination production function model, On Hager and Zhang's conjugate gradient method with guaranteed descent, On the Barzilai–Borwein gradient methods with structured secant equation for nonlinear least squares problems, A new descent algorithm using the three-step discretization method for solving unconstrained optimization problems, Globally convergent three-term conjugate gradient methods that use secant conditions and generate descent search directions for unconstrained optimization, Conjugate gradient methods based on secant conditions that generate descent search directions for unconstrained optimization, A structured diagonal Hessian approximation method with evaluation complexity analysis for nonlinear least squares, Unnamed Item, Some nonlinear conjugate gradient methods based on spectral scaling secant equations, A brief survey of methods for solving nonlinear least-squares problems, A conjugate gradient method with sufficient descent property, Scaled nonlinear conjugate gradient methods for nonlinear least squares problems, Structured spectral algorithm with a nonmonotone line search for nonlinear least squares

Uses Software

• minpack

Cites Work

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