Results 51 to 60 of about 281 (133)
Fractal and FractionalTo better simulate the prices of underlying assets and improve the accuracy of pricing financial derivatives, an increasing number of new models are being proposed.
Xu Chen +3 more
doaj +1 more source
Coupled Clustering in Hierarchical Matrices for the Oseen Problem
International Journal for Numerical Methods in Fluids, Volume 98, Issue 6, Page 751-765, June 2026.Fluid flow problems can be modelled by the Navier‐Stokes or, after linearization, by the Oseen equations. Their discretization results in linear systems in saddle point form which are typically very large and need to be solved iteratively. We propose a novel block structure for hierarchical matrices which is then used to build preconditioners for the ...
Jonas Grams, Sabine Le Borne
wiley +1 more source
A Preconditioned Majorization‐Minimization Method for ℓ2$$ {\ell}^2 $$‐ℓq$$ {\ell}^q $$ Minimization
Numerical Linear Algebra with Applications, Volume 33, Issue 3, June 2026.ABSTRACT The need to minimize a linear combination of an expression that involves an ℓq$$ {\ell}^q $$‐norm of a linear transformation of the computed solution and the ℓ2$$ {\ell}^2 $$‐norm of the residual error arises in image restoration as well as in statistics.
A. Buccini +3 more
wiley +1 more source
An Augmented Lagrangian Preconditioner for Navier–Stokes Equations With Runge–Kutta in Time
Numerical Linear Algebra with Applications, Volume 33, Issue 3, June 2026.ABSTRACT We consider an implicit Runge–Kutta method for the numerical time integration of the nonstationary incompressible Navier–Stokes equations. This yields a sequence of nonlinear problems to be solved for the stages of the Runge–Kutta method. The resulting nonlinear system of differential equations is discretized using a finite element method.
Santolo Leveque +2 more
wiley +1 more source
Inexact Krylov Subspace Methods for Linear Systems [PDF]
SIAM Journal on Matrix Analysis and Applications, 2004 This paper is devoted to the impact of perturbations of the matrix-vector product in various Krylov subspace solvers. This problem is related to the rounding errors analysis of Krylov subspace methods since in the latter case an inexact matrix-vector product is one source of errors.
Eshof, J. van den, Sleijpen, G.L.G.
openaire +5 more sources
Gram Decay and Intrinsic Dimensions of Krylov Subspaces
Numerical Linear Algebra with Applications, Volume 33, Issue 3, June 2026.ABSTRACT Krylov subspace methods solve large sparse linear systems Ax=b$$ Ax=b $$ by building a sequence of polynomial approximations to A−1b$$ {A}^{-1}b $$ from successive matrix‐vector products. In finite precision, the number of numerically independent directions that can be extracted from this sequence is bounded by the intrinsic information ...
Stephen J. Thomas
wiley +1 more source
Krylov Subspace Recycling for Evolving Structures
CoRR, 2020 Krylov subspace recycling is a powerful tool for solving long series of large, sparse linear systems that change slowly. In PDE constrained shape optimization, these appear naturally, as hundreds or more optimization steps are needed with only small changes in the geometry.
Matthias Bolten +2 more
openaire +2 more sources
Preserving Symmetry in Preconditioned Krylov Subspace Methods [PDF]
SIAM Journal on Scientific Computing, 1998 The authors consider the problem of solving linear systems of equations with coefficient matrices which are ``nearly'' (very close to be) symmetric and when symmetric positive definite preconditioners are used. They show that it is possible to improve upon the standard practice of using nonsymmetric preconditioners for that matrices along with a left ...
Tony F. Chan +3 more
openaire +2 more sources
Simultaneous Inversion for Underactuated Mechanical Systems with Servo‐Constraints
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT The dynamic inversion of underactuated mechanical systems can be formulated in the servo‐constraint framework using a set of differential‐algebraic equations (DAEs). In case of a high differentiation index, the inversion‐based feedforward control design poses significant challenges.
Tengman Wang
wiley +1 more source
Iterative Krylov Subspace Methods for Linear Port‐Hamiltonian Systems
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT In this work, we present a structure‐preserving Krylov subspace iteration scheme for solving the equation systems that arise from the Gauss integration of linear energy‐conserving and dissipative differential systems (e.g., Poisson systems, gradient systems, and port‐Hamiltonian systems).
Stefan Maier, Nicole Marheineke
wiley +1 more source