@Article{EAJAM-12-874, author = {Yang , Ai-Li and Chen , Xue-Qi}, title = {A Partially Greedy Randomized Extended Gauss-Seidel Method for Solving Large Linear Systems}, journal = {East Asian Journal on Applied Mathematics}, year = {2022}, volume = {12}, number = {4}, pages = {874--890}, abstract = {

A greedy Gauss-Seidel based on the greedy Kaczmarz algorithm and aimed to find approximations of the solution $A^†b$ of systems of linear algebraic equations with a full column-rank coefficient matrix $A$ is proposed. Developing this approach, we introduce a partially greedy randomized extended Gauss-Seidel method for finding approximate least-norm least-squares solutions of column-rank deficient linear systems. The convergence of the methods is studied. Numerical experiments show that the proposed methods are robust and efficient.

}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.300921.170422}, url = {http://global-sci.org/intro/article_detail/eajam/20888.html} }