.png){kind=icon}
.png){kind=icon}
Return
Normalized explicit finite element approximate inverse preconditioning
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compstruc.2004.04.010.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Normalized explicit approximate inverse matrix techniques for computing explicitly various families of normalized approximate inverses based on normalized approximate factorization procedures for solving sparse linear systems, which are derived from the finite difference and finite element discretization of partial differential equations are presented. Normalized explicit preconditioned conjugate gradient-type schemes in conjunction with normalized approximate inverse matrix techniques are presented for the efficient solution of linear and non-linear systems. Theoretical estimates on the rate of convergence and computational complexity of the normalized explicit preconditioned conjugate gradient method are also presented. Applications of the proposed methods on characteristic linear and non-linear problems are discussed and numerical results are given. (C) 2004 Elsevier Ltd. All rights reserved.
Keywords:
initial/boundary value problems
finite element method
finite difference method
non-linear systems
sparse linear systems
normalized approximate factorization procedures
normalized approximate inverse finite element matrix techniques
preconditioning
conjugate gradient schemes
rate of convergence and computational complexity
parallel iterative methods
parallel computations
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
C
IF:
4.8
Papers:
6.2K
Citations:
1.7W
Organization
No organization information available