Extending quasi-GMRES method to solve generalized Sylvester tensor equations via the Einstein product

This paper aims to extend a Krylov subspace technique based on an in-complete orthogonalization of Krylov tensors (as a multidimensional exten-sion of the common Krylov vectors) to solve generalized Sylvester tensor equations via the Einstein product. First, we obtain the tensor form of the quasi-GMRES method, and then we lead to the direct variant of the proposed algorithm. This approach has the great advantage that it uses previous data in each iteration and has a low computational cost. More-over, an upper bound for the residual norm of the approximate solution is found. Finally, several experimental problems are given to show the acceptable accuracy and efficiency of the presented method.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-09-01
DOI
https://doi.org/10.22067/ijnao.2024.87481.1418
Citations
1
Primary Topic
Tensor decomposition and applications
Type
article
Field-Weighted Citation Impact
0.33
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article

Extending quasi-GMRES method to solve generalized Sylvester tensor equations via the Einstein product

1 citations
SHILAP Revista de lepidopterología
Tensor decomposition and applications
0.33
article

Extending quasi-GMRES method to solve generalized Sylvester tensor equations via the Einstein product

article en
1 citations

Abstract

This paper aims to extend a Krylov subspace technique based on an in-complete orthogonalization of Krylov tensors (as a multidimensional exten-sion of the common Krylov vectors) to solve generalized Sylvester tensor equations via the Einstein product. First, we obtain the tensor form of the quasi-GMRES method, and then we lead to the direct variant of the proposed algorithm. This approach has the great advantage that it uses previous data in each iteration and has a low computational cost. More-over, an upper bound for the residual norm of the approximate solution is found. Finally, several experimental problems are given to show the acceptable accuracy and efficiency of the presented method.

SHILAP Revista de lepidopterología
Openalex Percentile: Top 44%
Tensor decomposition and applications
0.33
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