摘要
基于一种有效的从系数矩阵中选取两个工作行的贪婪概率准则,提出一类求解大型稀疏线性系统的贪婪双子空间随机Kaczmarz方法。理论证明该方法收敛到相容线性系统的最小范数解,而且该方法的理论收敛因子小于原始双子空间随机Kaczmarz方法的收敛因子。数值实验表明,该方法在求解性能方面较原始双子空间随机Kaczmarz方法更具优势。
Based on an effective greedy probability criterion for selecting two working rows from a coefficient matrix, a greedy two-subspace randomized Kaczmarz method for solving large sparse linear systems is proposed. The theoretical analysis shows that this method converges to the minimal-norm solution of consistent linear systems,and the convergence factor of the method is smaller than that of the original two-subspace randomized Kaczmarz method. The numerical experiments show that this method is superior to the original two-subspace randomized Kaczmarz method from the point of view of solution performance.
作者
荆燕飞
李彩霞
胡少亮
JING Yanfei;LI Caixia;HU Shaoliang(School of Mathematical Sciences,University of Electronic Science and Technology of China,Chengdu 611731,China;CAEP Software Center for High Performance Numerical Simulation,Beijing 100088,China)
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2021年第10期1473-1483,共11页
Journal of Tongji University:Natural Science
基金
国家自然科学基金(12071062,61772003)
科学挑战项目(TZ2016002—TZZT2019-B1.4)
电子科技大学理科实力提升计划。
