Global convergence of a modified CG-based method with Lipschitz continuity for unconstrained optimization and image restoration problems

IF 0.8 Q2 MATHEMATICS
Sulaiman Mohammed Ibrahim, P. Kaelo, Rabiu B. Yunus, Aceng Sambas
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引用次数: 0

Abstract

In this study, we extend the recently proposed RMIL* method to construct a new three-term conjugate gradient (TTCG) direction and show that it possesses sufficient descent property independently of the line search strategy used. We further prove the global convergence of the method using the famous Wolfe line search conditions. The computational efficiency of the algorithm (method) is tested on a set of unconstrained optimization and image restoration problems. The Findings of the numerical experiments show that the proposed method is robust and promising for both unconstrained minimization and application problems.

Abstract Image

无约束优化和图像恢复问题的一种改进的Lipschitz连续性算法的全局收敛性
在本研究中,我们扩展了最近提出的RMIL*方法,构造了一个新的三项共轭梯度(TTCG)方向,并证明它具有足够的下降特性,而不依赖于所使用的线搜索策略。利用著名的Wolfe线搜索条件进一步证明了该方法的全局收敛性。通过一组无约束优化和图像恢复问题,验证了该算法(方法)的计算效率。数值实验结果表明,该方法具有较强的鲁棒性和较好的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Afrika Matematika
Afrika Matematika MATHEMATICS-
CiteScore
2.00
自引率
9.10%
发文量
96
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