Geometric aspects of the theory of Krylov subspace methods
By Michael C. Eiermann, Oliver G. Ernst. Acta Numerica, 2001
135 citations recorded by the source corpus.
Subfields: Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/c11b791298e3b40d1b7ed52f736c6a41f713a749
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In Atomic and Molecular Physics, and Optics
- Valeria Simoncini
- Daniel B. Szyld
- Marcus V. Sarkis
- Christian E. Schaerer
- Xiuhong Du
- Maxim A. Olshanskii
- James Martens
- Bart Vandereycken
In Computational Theory and Mathematics
- Daniel B. Szyld
- Valeria Simoncini
- Marcus V. Sarkis
- Christian E. Schaerer
- Xiuhong Du
- Peter Benner
- Bart Vandereycken
- Maxim A. Olshanskii
In Electrical and Electronic Engineering
- Daniel B. Szyld
- Marcus V. Sarkis
- Christian E. Schaerer
- Paolo Novati
- Xiuhong Du
- Valeria Simoncini
- Igor Moret
- Marlis Hochbruck
Citations in the corpus
- Recent computational developments in Krylov subspace methods for linear systems (2007, methodology): “the analysis by Eiermann and Ernst [92].”
- INEXACT AND TRUNCATED PARAREAL-INTIME KRYLOV SUBSPACE METHODS FOR PARABOLIC OPTIMAL CONTROL PROBLEMS (2012, methodology): “…the approximation u m = u 0 + V m x m is computed, where x m is the solution of the linear system (3.3) H m x = βe 1 , with β = r 0 , r 0 = b − Hu 0 , H m = V T m HV m is an m × m upper Hessenberg matrix, and e 1 is the first Euclidean vector; see, e.g., [9] [26] [27] [30] for more details on FOM.”
- RD-Rational Approximations of the Matrix Exponential (2004, background): “, [26], [12]), the rate of decay of the hj+1,j ’ s plays a crucial role in the effectiveness of Krylov approximations methods.”
- Neurobiology of Aging: Contents (2005, unknown): “For additional analyses of Krylov subspace methods in terms of projections see, e.g., Barth and Manteuffel (1994) and Eiermann and Ernst (2001).”