Results 71 to 80 of about 3,479 (214)
Smoothing-norm preconditioning for GMRES [PDF]
, 2004 When GMRES is applied to a discrete ill-posed problem with a square matrix, then the iterates can be considered as regularized solutions. We show how to precondition GMRES in such a way that the iterations take into account a smoothing norm for the ...
Jensen, Toke Koldborg +1 more
core
Advanced Intelligent Systems, Volume 8, Issue 4, April 2026.This study presents a new sampling‐based model predictive control minimizing reverse Kullback‐Leibler divergence to quickly find a local optimum. In addition, a modified Nesterov's acceleration method is introduced for faster convergence. The method is effective for real‐time simulations and real‐world operability improvement on a force‐driven mobile ...
Taisuke Kobayashi, Kota Fukumoto
wiley +1 more source
Generating Approximate Inverse Preconditioners for Sparse Matrices Using CUDA and GPGPU
Journal of Algorithms & Computational Technology, 2011 The problem of numerical solution of sparse matrix-based linear systems arises from many scientific applications. Iterative solvers and corresponding preconditioning techniques are usually adopted.
Shiming Xu +3 more
doaj +1 more source
Energy‐Efficient Microwave Sintering of Binder‐Jetted Alumina
Journal of the American Ceramic Society, Volume 109, Issue 4, April 2026.Flowchart showing the developed microwave (MW) method to rapidly (∼48x faster) and uniformly heat binder‐jet 3D‐printed Al2O3 complex geometries with ∼96% lower energy consumption over conventional sintering process. Multiphysics simulations investigated the effects of susceptor configurations for thermal‐field control.
Bashu Aman +6 more
wiley +1 more source
, 1994 \begin{abstract} \noindent The GMRES algorithm minimizes $\norm{p(A)b}$ over polynomials $p$ of degree $n$ normalized at $z=0$. The ideal GMRES problem is obtained if one considers minimization of $\norm{p(A)}$ instead.
Kim-Chuan, Toh
core
Some properties of range restricted GMRES methods
, 2015 International audienceThe GMRES method is one of the most popular iterative schemes for the solution of large linear systems of equations with a square nonsingular matrix.
Reichel, Lothar +2 more
core +1 more source
Um Método Newton-Inexato com Estratégia Híbrida para Globalização
Trends in Computational and Applied Mathematics, 2008 Neste trabalho, o objetivo é propor um algoritmo Newton-inexato com propriedade de convergência global para resolução de sistemas não-lineares. Para a globalização, propomos uma abordagem híbrida, envolvendo, além de busca linear,o método de regiões de ...
R.G. Begiato, M.A. Gomes Ruggiero
doaj +1 more source
International Journal for Numerical Methods in Engineering, Volume 127, Issue 6, 30 March 2026.ABSTRACT The contribution deals with algebraic multigrid (AMG) based preconditioning methods for the iterative solution of a coupled linear system of equations arising in numerical simulations of failure of quasi‐brittle materials using generalized continuum approaches.
Nasser Alkmim +4 more
wiley +1 more source
Solution of Linear Systems by GMRES Method on Global Computing Platform
Journal of Algorithms & Computational Technology, 2007 By making use of a very large amount of unexploited computing resources, grid computing achieves high throughput computing. We present a classical parallel method GMRES (m) to solve large sparse linear systems utilizing a lightweight GRID system XtremWeb.
Haiwu He +3 more
doaj +1 more source
Accelerating Conjugate Gradient Solvers for Homogenization Problems With Unitary Neural Operators
International Journal for Numerical Methods in Engineering, Volume 127, Issue 5, 15 March 2026.ABSTRACT Rapid and reliable solvers for parametric partial differential equations (PDEs) are needed in many scientific and engineering disciplines. For example, there is a growing demand for composites and architected materials with heterogeneous microstructures.
Julius Herb, Felix Fritzen
wiley +1 more source