Results 11 to 20 of about 81,041 (236)
Preconditioners for Krylov subspace methods: An overview [PDF]
GAMM-Mitteilungen, 2020 When simulating a mechanism from science or engineering, or an industrial process, one is frequently required to construct a mathematical model, and then resolve this model numerically. If accurate numerical solutions are necessary or desirable, this can
J. Pearson, J. Pestana
semanticscholar +6 more sources
Pipelined, Flexible Krylov Subspace Methods [PDF]
SIAM Journal on Scientific Computing, 2015 We present variants of the Conjugate Gradient (CG), Conjugate Residual (CR), and Generalized Minimal Residual (GMRES) methods which are both pipelined and flexible.
P. Sanan, S. Schnepp, D. May
semanticscholar +4 more sources
Krylov Subspace Methods with Application in Incompressible Fluid Flow Solvers, 2018 Krylov subspace methods are widely used to solve large-scale linear systems, eigenvalue problems, and other matrix computations. In this mini-course, we will provide a brief overview of Krylov subspace methods focusing on the two widely used methods, the
A. Bruaset
semanticscholar +2 more sources
Biorthogonal rational Krylov subspace methods [PDF]
ETNA - Electronic Transactions on Numerical Analysis, 2019 Summary: A general framework for oblique projections of non-Hermitian matrices onto rational Krylov subspaces is developed. To obtain this framework we revisit the classical rational Krylov subspace algorithm and prove that the projected matrix can be written efficiently as a structured pencil, where the structure can take several forms such as ...
N. Buggenhout, M. Barel, R. Vandebril
semanticscholar +3 more sources
Flexible Krylov Methods for Edge Enhancement in Imaging [PDF]
Journal of Imaging, 2021 Many successful variational regularization methods employed to solve linear inverse problems in imaging applications (such as image deblurring, image inpainting, and computed tomography) aim at enhancing edges in the solution, and often involve non ...
Silvia Gazzola +2 more
doaj +2 more sources
A framework for deflated and augmented Krylov subspace methods [PDF]
SIAM Journal on Matrix Analysis and Applications, 2013 We consider deflation and augmentation techniques for accelerating the convergence of Krylov subspace methods for the solution of nonsingular linear algebraic systems.
André Gaul +4 more
core +5 more sources
Flexible Inner-Outer Krylov Subspace Methods [PDF]
SIAM Journal on Numerical Analysis, 2002 Flexible Krylov methods refer to a class of methods which accept preconditioning that can change from one step to the next. An important special case is found when a fixed preconditioner is only approximated and the approximation changes from one step to the next.
Simoncini V., Szyld D.B.
openaire +4 more sources
KRYLOV SUBSPACE METHODS FOR SOLVING LARGE LYAPUNOV EQUATIONS [PDF]
SIAM Journal on Numerical Analysis, 1994 Published ...
JAIMOUKHA, IM, KASENALLY, EM
core +5 more sources
An Improved Reduced-Dimension Robust Capon Beamforming Method Using Krylov Subspace Techniques [PDF]
SensorsA reduced-dimension robust Capon beamforming method using Krylov subspace techniques (RDRCB) is a diagonal loading algorithm with low complexity, fast convergence and strong anti-interference ability.
Xiaolin Wang, Xihai Jiang, Yaowu Chen
doaj +2 more sources
Efficient preconditioning strategies for accelerating GMRES in block-structured nonlinear systems for image deblurring. [PDF]
PLoS ONEWe propose an efficient preconditioning strategy to accelerate the convergence of Krylov subspace methods, specifically for solving complex nonlinear systems with a block five-by-five structure, commonly found in cell-centered finite difference ...
Rizwan Khalid +4 more
doaj +2 more sources