A hybrid three-term conjugate gradient projection method for constrained nonlinear monotone equations with applications

In this paper, based on the three-term conjugate gradient method and the hybrid technique, we propose a hybrid three-term conjugate gradient projection method by incorporating the adaptive line search for solving large-scale nonlinear monotone equations with convex constraints. The search direction...

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Vydáno v:Numerical algorithms Ročník 88; číslo 1; s. 389 - 418
Hlavní autoři: Yin, Jianghua, Jian, Jinbao, Jiang, Xianzhen, Liu, Meixing, Wang, Lingzhi
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.09.2021
Springer Nature B.V
Témata:
Adaptive search techniques
Algebra
Algorithms
Blurring
Computer Science
Conjugate gradient method
Constraints
Mathematical analysis
Methods
Numeric Computing
Numerical Analysis
Optimization
Original Paper
Robustness (mathematics)
Searching
Theory of Computation
Three-term conjugate gradient method
68U10
65K10
Convergence property
Compressed sensing
Derivative-free projection method
ISSN:1017-1398, 1572-9265
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Shrnutí:In this paper, based on the three-term conjugate gradient method and the hybrid technique, we propose a hybrid three-term conjugate gradient projection method by incorporating the adaptive line search for solving large-scale nonlinear monotone equations with convex constraints. The search direction generated by the proposed method is close to the one yielded by the memoryless BFGS method, and has the sufficient descent property and the trust region property independent of line search technique. Under some mild conditions, we establish the global convergence of the proposed method. Our numerical experiments show the effectiveness and robustness of the proposed method in comparison with two existing algorithms in the literature. Moreover, we show applicability and encouraging efficiency of the proposed method by extending it to solve sparse signal restoration and image de-blurring problems.
Bibliografie:ObjectType-Article-1
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ISSN:1017-1398
1572-9265
DOI:10.1007/s11075-020-01043-z