An accelerated descent CG algorithm with clustering the eigenvalues for large-scale nonconvex unconstrained optimization and its application in image restoration problems-Reference-Cited by-同舟云学术

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An accelerated descent CG algorithm with clustering the eigenvalues for large-scale nonconvex unconstrained optimization and its application in image restoration problems

Published:2024-02 Issue: Volume:437 Page:115454
ISSN:0377-0427
Container-title:Journal of Computational and Applied Mathematics
language:en
Short-container-title:Journal of Computational and Applied Mathematics

Author:

Wang Xiaoliang^ORCID,Yuan Gonglin

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Mathematics

Reference40 articles.

1. Convergence properties of nonlinear conjugate gradient methods;Dai;SIAM J. Optim.,2000

2. A survey of nonlinear conjugate gradient methods;Hager;Pacific J. Optim.,2006

3. Numerical comparison of conjugate gradient algorithms for unconstrained optimization;Andrei;Stud. Inform. Control,2007

4. A new Dai-Liao conjugate gradient method with optimal parameter choice;Zhang;Numer. Funct. Anal. Optim.,2019

5. New conjugacy conditions and related nonlinear conjugate gradient methods;Dai;Appl. Math. Optim.,2001

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1. Modified snake optimizer based multi-level thresholding for color image segmentation of agricultural diseases;Expert Systems with Applications;2024-12

2. A new approximate descent derivative-free algorithm for large-scale nonlinear symmetric equations;Computational and Applied Mathematics;2024-08-20

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