Conjugate-gradient-type iterative methods are formulated directly for T-product tensor equations, with finite-termination proofs and numerical demonstrations.
Tensor GMRES and Golub-Kahan Bidiagonalization methods via the Einstein product with applications to image and video processing
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
In the present paper, we are interested in developing iterative Krylov subspace methods in tensor structure to solve a class of multilinear systems via Einstein product. In particular, we develop global variants of the GMRES and Gloub--Kahan bidiagonalization processes in tensor framework. We further consider the case that mentioned equation may be possibly corresponds to a discrete ill-posed problem. Applications arising from color image and video restoration are included.
fields
math.NA 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Efficient iterative techniques for solving tensor problems with the T-product
Conjugate-gradient-type iterative methods are formulated directly for T-product tensor equations, with finite-termination proofs and numerical demonstrations.