New three-term conjugate gradient algorithm for solving monotone nonlinear equations and signal recovery problems

被引：1

作者：

Abubakar, Auwal Bala ^{[1
,2
,3
]}

Kumam, Poom ^{[1
,6
]}

Liu, Jinkui ^{[4
]}

Mohammad, Hassan ^{[2
]}

Tammer, Christiane ^{[5
]}

机构：

[1] King Mongkuts Univ Technol Thonburi KMUTT, Fac Sci, Ctr Excellence Theoret & Computat Sci TaCS CoE, Fixed Point Res Lab,Fixed Point Theory & Applicat, Bangkok, Thailand

[2] Bayero Univ, Fac Phys Sci, Dept Math Sci, Numer Optimizat Res Grp, Kano, Nigeria

[3] Sefako Makgatho Hlth Sci Univ, Dept Math & Appl Math, Pretoria, South Africa

[4] Chongqing Three Gorges Univ, Sch Math & Stat, Chongqing, Peoples R China

[5] Martin Luther Univ Halle Wittenberg, Inst Math, Fac Nat Sci 2, Halle, Saale, Germany

[6] King Mongkuts Univ Technol Thonburi KMUTT, Fac Sci, Ctr Excellence Theoret & Computat Sci TaCS CoE, Fixed Point Res Lab,Fixed Point Theory & Applicat, 126 Pracha Uthit Rd, Bangkok 10140, Thailand

来源：

INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS | 2023年 / 100卷 / 10期

关键词：

Nonlinear equations; conjugate gradient; projection map; signal recovery; PROJECTION METHOD; VARIATIONAL INEQUALITY; DESCENT; SYSTEMS; SPARSE;

D O I：

10.1080/00207160.2023.2239947

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This work presents a new three-term projection algorithm for solving nonlinear monotone equations. The paper is aimed at constructing an efficient and competitive algorithm for finding approximate solutions of nonlinear monotone equations. This is based on a new choice of the conjugate gradient direction which satisfies the sufficient descent condition. The convergence of the algorithm is shown under Lipschitz continuity and monotonicity of the involved operator. Numerical experiments presented in the paper show that the algorithm needs a less number of iterations in comparison with existing algorithms. Furthermore, the proposed algorithm is applied to solve signal recovery problems.

引用

页码：1992 / 2013

页数：22

共 46 条

[1]

Abubakar Auwal Bala, 2022, 2022 12th International Conference on Information Science and Technology (ICIST), P1, DOI 10.1109/ICIST55546.2022.9926859

[2]

Abubakar A.B., 2022, MATH METHODS APPL SC

[3] A hybrid approach for finding approximate solutions to constrained nonlinear monotone operator equations with applications [J].