Results 21 to 30 of about 481 (184)

Comparison of Algebraic Multigrid Preconditioners for Solving Helmholtz Equations

open access: yesJournal of Applied Mathematics, 2012
An algebraic multigrid (AMG) with aggregation technique to coarsen is applied to construct a better preconditioner for solving Helmholtz equations in this paper.
Dandan Chen, Ting-Zhu Huang, Liang Li
doaj   +1 more source

The Mixed Finite Element Multigrid Method for Stokes Equations

open access: yesThe Scientific World Journal, 2015
The stable finite element discretization of the Stokes problem produces a symmetric indefinite system of linear algebraic equations. A variety of iterative solvers have been proposed for such systems in an attempt to construct efficient, fast, and robust
K. Muzhinji, S. Shateyi, S. S. Motsa
doaj   +1 more source

Algebraic Multi-Grid Based Multi-Focus Image Fusion Using Watershed Algorithm

open access: yesIEEE Access, 2018
This paper proposes a new multi-focus image fusion method named AMGW, and it is based on algebraic multi-grid (AMG) algorithm and watershed segmentation method.
Ying Huang   +3 more
doaj   +1 more source

The hp-version of the least-squares collocation method with integral collocation for solving a biharmonic equation [PDF]

open access: yesVestnik Samarskogo Gosudarstvennogo Tehničeskogo Universiteta. Seriâ: Fiziko-Matematičeskie Nauki, 2022
A new algorithm for the numerical solution of the biharmonic equation is developed. It is based on the first implemented hp-version of the least-squares collocation method (hp-LSCM) with integral collocations for a fourth-order elliptic equation in ...
Vasily P. Shapeev   +2 more
doaj   +1 more source

A Spectral-Spatial Classification of Hyperspectral Images Based on the Algebraic Multigrid Method and Hierarchical Segmentation Algorithm

open access: yesRemote Sensing, 2016
The algebraic multigrid (AMG) method is used to solve linear systems of equations on a series of progressively coarser grids and has recently attracted significant attention for image segmentation due to its high efficiency and robustness. In this paper,
Haiwei Song, Yi Wang
doaj   +1 more source

On Optimal Algebraic Multigrid Methods

open access: yesCoRR, 2019
In this note we present an alternative way to obtain optimal interpolation operators for two-grid methods applied to Hermitian positive definite linear systems. Falgout and Vassilevski in [SIAM J. Numer. Anal, 42 (2004), pp. 1669-1693] and Zikatanov [Numer. Linear Algebra Appl., 15 (2008), pp.
Luis García Ramos, Reinhard Nabben
openaire   +2 more sources

Fast Solution of 3-D Eddy-Current Problems in Multiply Connected Domains by a, v-φ and t-φ Formulations With Multigrid-Based Algorithm for Cohomology Generation

open access: yesIEEE Access, 2022
The fast solution of three-dimensional eddy current problems is still an open problem, especially when real-size finite element models with millions of degrees of freedom are considered.
Federico Moro   +4 more
doaj   +1 more source

Description and implementation of an algebraic multigrid preconditioner for H1-conforming finite element schemes

open access: yesUniciencia, 2020
This paper presents detailed aspects regarding the implementation of the Finite Element Method (FEM) to solve a Poisson’s equation with homogeneous boundary conditions.
Helen Guillén-Oviedo   +3 more
doaj   +1 more source

A new multilevel smoothing method for wavelet-based algebraic multigrid poisson problem solver

open access: yesJournal of Microwaves, Optoelectronics and Electromagnetic Applications
In contrast to the standard algebraic multigrid, the Wavelet-based Algebraic Multigrid method relies more strongly on the smoothing method because the coarse spaces are chosen a priori. So, it is very important to develop new smoother methods, especially
Fabio Henrique Pereira   +2 more
doaj   +1 more source

Algebraic multigrid support vector machines [PDF]

open access: yesCoRR, 2016
The support vector machine is a flexible optimization-based technique widely used for classification problems. In practice, its training part becomes computationally expensive on large-scale data sets because of such reasons as the complexity and number of iterations in parameter fitting methods, underlying optimization solvers, and nonlinearity of ...
Ehsan Sadrfaridpour   +5 more
openaire   +2 more sources

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