In recent years, a number of preconditioners have been applied to solve the linear systems with Gauss-Seidel method (see [1-7,10-12,14-16]). In this paper we use S l instead of (S + S m) and compare ...

The Gauss-Seidel method is an iterative technique for solving a system of linear equations. This particular implementation leverages the concept of sparse matrices to efficiently manage large datasets ...

Abstract: The Gauss-Seidel method is very efficient for solving problems such as tightly-coupled constraints with possible redundancies. However, the underlying algorithm is inherently sequential.

Abstract: In the field of operator equations, solving the inner inverses is essential. In this paper, based on the Lagrangian function a class of block Gauss-Seidel methods is proposed, which contains ...

This Module is Numerical analysis, an area of mathematics and computer science that creates, analyzes, and implements algorithms for obtaining numerical solutions to problems involving continuous ...

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 ...

Gauss-Seidel Anchored Value Iteration (GS-Anc-VI) combines anchoring with Gauss-Seidel updates to improve convergence rates for finite state-action spaces, offering fast convergence for Bellman ...