多值映射不动点集凸最小化的混合最陡下降算法

IF 1.4 4区数学 Q1 MATHEMATICS Carpathian Journal of Mathematics Pub Date : 2022-07-30 DOI:10.37193/cjm.2023.01.21

Yasir Arfat, P. Kumam, M. A. A. Khan, Y. Cho

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引用次数: 0

摘要

在Hilbert空间中，我们证明了混合最速下降算法强收敛于有限族多值半压缩映射的不动点集上的凸最小化问题的解。我们还提供了关于所提出的算法的可行性的数值结果以及可能的应用。

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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A Hybrid Steepest-Descent Algorithm for Convex Minimization Over the Fixed Point Set of Multivalued Mappings

In the setting of Hilbert spaces, we show that a hybrid steepest-descent algorithm converges strongly to a solution of a convex minimization problem over the fixed point set of a finite family of multivalued demicontractive mappings. We also provide numerical results concerning the viability of the proposed algorithm with possible applications.

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来源期刊

Carpathian Journal of Mathematics MATHEMATICS, APPLIED-MATHEMATICS

CiteScore

2.40

自引率

7.10%

发文量

审稿时长

>12 weeks

期刊介绍： Carpathian Journal of Mathematics publishes high quality original research papers and survey articles in all areas of pure and applied mathematics. It will also occasionally publish, as special issues, proceedings of international conferences, generally (co)-organized by the Department of Mathematics and Computer Science, North University Center at Baia Mare. There is no fee for the published papers but the journal offers an Open Access Option to interested contributors.