An approximate gradient-type method for nonlinear symmetric equations with convex constraints
Author:
Funder
Chongqing Research Program of Basic Research and Frontier Technology
Chongqing Three Gorges University
Publisher
Elsevier BV
Subject
Applied Mathematics,Computational Mathematics
Reference21 articles.
1. A globally and superlinearly convergent Gauss–Newton-based BFGS method for symmetric nonlinear equations;Li;SIAM J. Numer. Anal.,1999
2. Norm descent conjugate gradient methods for solving symmetric nonlinear equations;Xiao;J. Global Optim.,2015
3. A nonlinear conjugate gradient algorithm with an optimal property and an improved wolfe line search;Dai;SIAM J. Optim.,2013
4. New three-term conjugate gradient method with guaranteed global convergence;Liu;Int. J. Comput. Math.,2014
5. A norm descent derivative-free algorithm for solving large-scale nonlinear symmetric equations;Liu;J. Comput. Appl. Math.,2018
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