Results 71 to 80 of about 78,319 (219)
Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.ABSTRACT We derive eigenvalue bounds for symmetric block‐tridiagonal multiple saddle‐point systems preconditioned with block‐diagonal Schur complement matrices. This analysis applies to an arbitrary number of blocks and accounts for the case where the Schur complements are approximated, generalizing the findings in [11, Bergamaschi et al., Linear ...
Marco Pilotto +2 more
wiley +1 more source
The Use of Restarted Krylov Methods for Large Sparse Least Squares Problems
Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.ABSTRACT The use of restarted Krylov methods for solving large sparse linear least squares problems suffers from certain inherited difficulties. One of them arises in ill‐conditioned problems, when part of the residual vector is spanned by singular vectors that correspond to small singular values.
Achiya Dax
wiley +1 more source
A Class of Preconditioners for Large Indefinite Linear Systems, as by-product of Krylov subspace Methods: Part II [PDF]
In this paper we consider the parameter dependent class of preconditioners M(a,d,D) defined in the companion paper The latter was constructed by using information from a Krylov subspace method, adopted to solve the large symmetric linear system Ax = b ...
Massimo Roma, Giovanni Fasano
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Mixed Precision Augmented GMRES
Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.ABSTRACT We aim to accelerate the restarted generalized minimal residual (GMRES) method for the solutions of linear systems by combining two types of techniques. On the one hand, mixed precision GMRES algorithms, which use lower precision in certain steps of the inner cycles, offer significant reductions in computational and memory costs.
Yongseok Jang +2 more
wiley +1 more source
Studies in Applied Mathematics, Volume 157, Issue 2, August 2026.ABSTRACT We consider the extended Korteweg–de Vries (eKdV) equation as a model for long moderately nonlinear surface water waves and use it to describe the evolution of initial conditions generating solitary waves with and without significant dispersive radiation, as well as cases of pure dispersive radiation without any solitary waves.
Benjamin Martin +2 more
wiley +1 more source
Fast sampling from a Gaussian Markov random field using Krylov subspace approaches [PDF]
, 2008 Many applications in spatial statistics, geostatistics and image analysis require efficient techniques for sampling from large Gaussian Markov random fields (GMRFs).
Simpson, Daniel P. +2 more
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Krylov complexity of supersymmetric SYK models
Journal of High Energy PhysicsWe study the effect of supersymmetry breaking on Krylov complexity in the N = 2 $$ \mathcal{N}=2 $$ SYK model under irrelevant and mass deformations of the Hamiltonian. The irrelevant deformation breaks N = 2 $$ \mathcal{N}=2 $$ supersymmetry down to N =
James Chryssanthacopoulos, David Vegh
doaj +1 more source
Performance of relaxed iterative methods for image deblurring problems
Journal of Algorithms & Computational Technology, 2019 In this paper, we consider performance of relaxation iterative methods for four types of image deblurring problems with different regularization terms.
Jae H Yun
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A Matrix‐Free, Scalable, and Robust Implicit Material Point Method
International Journal for Numerical Methods in Engineering, Volume 127, Issue 14, 30 July 2026.ABSTRACT An implicit material point method is presented using a new dynamic relaxation solver, allowing for a simple and efficient quasi‐static formulation that may be readily implemented in existing explicit‐dynamic codes. The use of dynamic relaxation and aggregation is shown to produce an extremely robust material point method scheme, with good ...
Sam J. V. Sutcliffe +5 more
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KRYLOV SUBSPACE ACCELERATION OF WAVEFORM RELAXATION ∗
, 2008 . In this paper we describe and analyze Krylov subspace techniques for accelerating the convergence of waveform relaxation for solving time dependent problems. A new class of accelerated waveform methods, convolution Krylov subspace methods, is presented.
Andrew Lumsdaine, Deyun Wu
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