GMRES with Singular Vector Approximations
For researchers solving linear systems, this method offers a new augmentation strategy, but the improvements are incremental and lack concrete numerical comparisons.
The paper proposes a GMRES method that augments Krylov subspaces with approximate right singular vectors to suppress error norms in linear systems. Numerical experiments show improvements over standard GMRES and GMRES with eigenvectors on benchmark matrices.
This paper has proposed the GMRES that augments Krylov subspaces with a set of approximate right singular vectors. The proposed method suppresses the error norms of a linear system of equations. Numerical experiments comparing the proposed method with the Standard GMRES and GMRES with eigenvectors methods[3] have been reported for benchmark matrices.