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Low-rank improvements of two-level grid preconditioned matrices
- 1.0495392 - ÚGN 2019 RIV NL eng J - Journal Article
Axelsson, Owe - Blaheta, Radim
Low-rank improvements of two-level grid preconditioned matrices.
Journal of Computational and Applied Mathematics. Roč. 340, č. 1 (2018), s. 432-442. ISSN 0377-0427. E-ISSN 1879-1778
R&D Projects: GA MŠMT LQ1602; GA MŠMT LD15105
Institutional support: RVO:68145535
Keywords : two-level grids * approximate Schur complement inverse * low-rank correction * parallelizable methods
OECD category: Applied mathematics
Impact factor: 1.883, year: 2018 ; AIS: 0.661, rok: 2018
Result website:
https://www.sciencedirect.com/science/article/pii/S0377042717304582DOI: https://doi.org/10.1016/j.cam.2017.09.027
As an alternative to basic two-level and multilevel iteration preconditioners for elliptic partial differential equations, it is shown that low-rank approximations, based on approximate eigenvectors to the largest eigenvalues of the inverse two-level Schur complement matrix, can give arbitrarily accurate preconditioners that hold uniformly with respect to mesh sizes. The methods are particularly efficient for problems with multiple right hand sides.
Permanent Link: http://hdl.handle.net/11104/0288379
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