Results 151 to 160 of about 16,256 (203)
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Truncation Strategies for Optimal Krylov Subspace Methods
SIAM Journal on Numerical Analysis, 1999Summary: Optimal Krylov subspace methods like GMRES and GCR have to compute an orthogonal basis for the entire Krylov subspace to compute the minimal residual approximation to the solution. Therefore, when the number of iterations becomes large, the amount of work and the storage requirements become excessive. In practice one has to limit the resources.
Eric de Sturler
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Macromodelling oscillators using krylov-subspace methods
Asia and South Pacific Conference on Design Automation, 2006., 2006We present an efficient method for automatically extracting unified amplitude/phase macromodels of arbitrary oscillators from their SPICE-level circuit descriptions. Such comprehensive oscillator macromodels are necessary for accuracy when speeding up simulation of higher-level circuits/systems, such as PLLs, in which oscillators are embedded. Standard
Xiaolue Lai, Jaijeet Roychowdhury
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Spectral Variants of Krylov Subspace Methods
Numerical Algorithms, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Molina, Brígida, Raydan, Marcos
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Projection Methods in Krylov Subspaces
Journal of Mathematical Sciences, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Error-Minimizing Krylov Subspace Methods
SIAM Journal on Scientific Computing, 1994This paper first introduces generalized conjugate gradient methods which specialize to error minimizing procedures as well as to residual minimizing methods. General minimum error methods are then introduced, and the two method classes are compared.
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On Moment Methods in Krylov Subspaces
Doklady Mathematics, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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On tensor tubal-Krylov subspace methods
Linear and Multilinear Algebra, 2021In this paper, we will introduce some new tubal-Krylov subspace methods for solving linear tensor equations. Using the well known tensor T-product, we will in particular define the tensor tubal-global GMRES that could be seen as a generalization of the global GMRES. We also give a new tubal-version of the tensor Golub–Kahan algorithm.
El Ichi, Alaa +2 more
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Multigrid Incomplete Factorization Methods in Krylov Subspaces
Journal of Mathematical Sciences, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Analysis of Augmented Krylov Subspace Methods
SIAM Journal on Matrix Analysis and Applications, 1997``Augmented Krylov methods'' are studied theoretically. These methods for solving a linear system are projection methods in which the subspace of projection is of the form \(K = K_{m} + W\), where \(K_{m}\) is the standard Krylov subspace, which is augmented by another subspace \(W\). The subspace \(W\) can be chosen in different ways.
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