Results 41 to 50 of about 2,786 (218)

A Broadband Enhanced Structure-Preserving Reduced-Order Interconnect Macromodeling Method for Large-Scale Equation Sets of Transient Interconnect Circuit Problems

open access: yesEnergies, 2020
In the transient analysis of an engineering power electronics device, the order of its equivalent circuit model is excessive large. To eliminate this issue, some model order reduction (MOR) methods are proposed in the literature.
Ning Wang, Huifang Wang, Shiyou Yang
doaj   +1 more source

Coupled Clustering in Hierarchical Matrices for the Oseen Problem

open access: yesInternational 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

Compact models for wireless systems [PDF]

open access: yes, 2010
For the design and analysis of wireless systems, complex simulations are required and performed. Model order reduction techniques enable greater efficiencies to be achieved and concomitantly, a reduction in memory-resource usage. However, maintaining a
Condon, Marissa, Grahovski, Georgi G.
core  

A Preconditioned Majorization‐Minimization Method for ℓ2$$ {\ell}^2 $$‐ℓq$$ {\ell}^q $$ Minimization

open access: yesNumerical 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

Krylov SSP Integrating Factor Runge–Kutta WENO Methods

open access: yesMathematics, 2021
Weighted essentially non-oscillatory (WENO) methods are especially efficient for numerically solving nonlinear hyperbolic equations. In order to achieve strong stability and large time-steps, strong stability preserving (SSP) integrating factor (IF ...
Shanqin Chen
doaj   +1 more source

An Augmented Lagrangian Preconditioner for Navier–Stokes Equations With Runge–Kutta in Time

open access: yesNumerical 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

Generalized Preconditioned MHSS Method for a Class of Complex Symmetric Linear Systems

open access: yesAbstract and Applied Analysis, 2014
Based on the modified Hermitian and skew-Hermitian splitting (MHSS) and preconditioned MHSS (PMHSS) methods, a generalized preconditioned MHSS (GPMHSS) method for a class of complex symmetric linear systems is presented.
Cui-Xia Li, Yan-Jun Liang, Shi-Liang Wu
doaj   +1 more source

A Method of Indefinite Krylov Subspace for Eigenvalue Problem [PDF]

open access: yesMathematical Problems in Engineering, 2018
We describe an indefinite state of Arnoldi’s method for solving the eigenvalues problems. In the following, we scrutinize the indefinite state of Lanczos’ method for solving the eigenvalue problems and we show that this method for the J-Hermitian matrices works much better than Arnoldi’s method.
M. Aliyari, M. Ghasemi Kamalvand
openaire   +1 more source

Gram Decay and Intrinsic Dimensions of Krylov Subspaces

open access: yesNumerical 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 methods in the electronic industry [PDF]

open access: yes, 2004
Summary. Krylov subspace methods are well-known for their nice properties, but they have to be implemented with care. In this article the mathematical consequences encountered during implementation of Krylov subspace methods in an existing layout ...
Schilders, W.H.A.   +5 more
core  

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