A Two-Step Spectral Gradient Projection Method for System of Nonlinear Monotone Equations and Image Deblurring Problems

被引:32
作者
Awwal, Aliyu Muhammed [1 ,2 ]
Wang, Lin [3 ]
Kumam, Poom [1 ,4 ]
Mohammad, Hassan [5 ]
机构
[1] King Mongkuts Univ Technol Thonburi KMUTT, Fac Sci, Dept Math, KMUTTFixed Point Res Lab, Room SCL 802 Fixed Point Lab,Sci Lab Bldg, Bangkok 10140, Thailand
[2] Gombe State Univ, Fac Sci, Dept Math, Gombe 760214, Nigeria
[3] Yunnan Univ Finance & Econ, Off Sci & Res, Kunming 650221, Yunnan, Peoples R China
[4] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung 40402, Taiwan
[5] Bayero Univ, Fac Phys Sci, Dept Math Sci, Kano 700241, Nigeria
来源
SYMMETRY-BASEL | 2020年 / 12卷 / 06期
关键词
spectral gradient method; nonlinear monotone equations; projection method; line search; image deblurring; THRESHOLDING ALGORITHM; BARZILAI;
D O I
10.3390/sym12060874
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this paper, we propose a two-step iterative algorithm based on projection technique for solving system of monotone nonlinear equations with convex constraints. The proposed two-step algorithm uses two search directions which are defined using the well-known Barzilai and Borwein (BB) spectral parameters.The BB spectral parameters can be viewed as the approximations of Jacobians with scalar multiple of identity matrices. If the Jacobians are close to symmetric matrices with clustered eigenvalues then the BB parameters are expected to behave nicely. We present a new line search technique for generating the separating hyperplane projection step of Solodov and Svaiter (1998) that generalizes the one used in most of the existing literature. We establish the convergence result of the algorithm under some suitable assumptions. Preliminary numerical experiments demonstrate the efficiency and computational advantage of the algorithm over some existing algorithms designed for solving similar problems. Finally, we apply the proposed algorithm to solve image deblurring problem.
引用
收藏
页数:20
相关论文
共 44 条
[21]   FIXED-POINTS BY A NEW ITERATION METHOD [J].
ISHIKAWA, S .
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY, 1974, 44 (01) :147-150
[22]   Nonmonotone spectral methods for large-scale nonlinear systems [J].
La Cruz, W ;
Raydan, M .
OPTIMIZATION METHODS & SOFTWARE, 2003, 18 (05) :583-599
[23]  
La Cruz W., 2004, RT0408 U CENTR VEN, P37
[24]   Spectral residual method without gradient information for solving large-scale nonlinear systems of equations [J].
La Cruz, William ;
Martinez, Jose Mario ;
Raydan, Marcos .
MATHEMATICS OF COMPUTATION, 2006, 75 (255) :1429-1448
[25]   A spectral algorithm for large-scale systems of nonlinear monotone equations [J].
La Cruz, William .
NUMERICAL ALGORITHMS, 2017, 76 (04) :1109-1130
[26]   A neural-network algorithm for solving nonlinear equation systems [J].
Li, Guimei ;
Zeng, Zhezhao .
2008 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY, VOLS 1 AND 2, PROCEEDINGS, 2008, :20-+
[27]   Two spectral gradient projection methods for constrained equations and their linear convergence rate [J].
Liu, Jing ;
Duan, Yongrui .
JOURNAL OF INEQUALITIES AND APPLICATIONS, 2015, :1-13
[28]   MEAN VALUE METHODS IN ITERATION [J].
MANN, WR .
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY, 1953, 4 (03) :506-510
[29]  
Mohammad H., 2017, B COMPUT APPL MATH, V5, P97
[30]   Structured Two-Point Stepsize Gradient Methods for Nonlinear Least Squares [J].
Mohammad, Hassan ;
Waziri, Mohammed Yusuf .
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 2019, 181 (01) :298-317