Krylov Subspace Methods for Linear Systems with Tensor Product Structure

@article{Kressner2010KrylovSM,
  title={Krylov Subspace Methods for Linear Systems with Tensor Product Structure},
  author={Daniel Kressner and Christine Tobler},
  journal={SIAM J. Matrix Analysis Applications},
  year={2010},
  volume={31},
  pages={1688-1714}
}
The numerical solution of linear systems with certain tensor product structures is considered. Such structures arise, for example, from the finite element discretization of a linear PDE on a d-dimensional hypercube. Linear systems with tensor product structure can be regarded as linear matrix equations for d = 2 and appear to be their most natural extension for d > 2. A standard Krylov subspace method applied to such a linear system suffers from the curse of dimensionality and has a… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 47 extracted citations

Low-rank updates of matrix functions

SIAM J. Matrix Analysis Applications • 2018
View 1 Excerpt

References

Publications referenced by this paper.
Showing 1-10 of 25 references

Efficient MATLAB Computations with Sparse and Factored Tensors

SIAM J. Scientific Computing • 2007
View 5 Excerpts
Highly Influenced

A New Iterative Method for Solving Large-Scale Lyapunov Matrix Equations

SIAM J. Scientific Computing • 2007
View 4 Excerpts
Highly Influenced

Entwicklungen nach Exponentialsummen

W. Hackbusch
2008
View 1 Excerpt

Extended Arnoldi methods for large Sylvester matrix equations

M. Heyouni
Technical report L.M.P.A. • 2008
View 1 Excerpt

Krylov subspace methods for large linear systems with tensor product structure

C. Tobler
Master’s thesis, ETH Zürich, September • 2008
View 1 Excerpt

Similar Papers

Loading similar papers…