Greedy Randomized Kaczmarz with momentum method for nonlinear equation

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED
Li Liu, Wei-Guo Li, Li-Li Xing, Wen-Di Bao
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引用次数: 0

Abstract

Based on the nonlinear greedy randomized Kaczmarz (NGRK) method and the heavy ball method, a nonlinear greedy randomized Kaczmarz with momentum (NGRKm) method is presented for solving large nonlinear systems. Furthermore, the convergence of the NGRKm method is proved and the corresponding numerical experiments show the effectiveness of the NGRKm method.
非线性方程的贪婪随机卡茨马兹动量法
在非线性贪心随机卡兹马兹(NGRK)方法和重球方法的基础上,提出了一种求解大型非线性系统的非线性贪心随机卡兹马兹(NGRKm)方法。此外,还证明了 NGRKm 方法的收敛性,并通过相应的数值实验展示了 NGRKm 方法的有效性。
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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