高斯-赛德尔法
斜格
数学
趋同(经济学)
基质(化学分析)
应用数学
高斯
数学分析
迭代法
数学优化
物理
材料科学
量子力学
哲学
复合材料
经济增长
经济
语言学
作者
Weifeng Li,Pingping Zhang
出处
期刊:Journal of Applied Mathematics and Physics
[Scientific Research Publishing, Inc.]
日期:2023-01-01
卷期号:11 (04): 1036-1048
被引量:1
标识
DOI:10.4236/jamp.2023.114068
摘要
For the linear least squares problem with coefficient matrix columns being highly correlated, we develop a greedy randomized Gauss-Seidel method with oblique direction. Then the corresponding convergence result is deduced. Numerical examples demonstrate that our proposed method is superior to the greedy randomized Gauss-Seidel method and the randomized Gauss-Seidel method with oblique direction.
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