Approximate factoring of the inverse |
| |
Authors: | Mikko?Byckling Email author" target="_blank">Marko?HuhtanenEmail author |
| |
Institution: | 1.Institute of Mathematics,Helsinki University of Technology,Espoo,Finland |
| |
Abstract: | Computation of approximate factors for the inverse constitutes an algebraic approach to preconditioning large and sparse linear
systems. In this paper, the aim is to combine standard preconditioning ideas with sparse approximate inverse approximation,
to have dense approximate inverse approximations (implicitly). For optimality, the approximate factoring problem is associated
with a minimization problem involving two matrix subspaces. This task can be converted into an eigenvalue problem for a Hermitian
positive semidefinite operator whose smallest eigenpairs are of interest. Because of storage and complexity constraints, the
power method appears to be the only admissible algorithm for devising sparse–sparse iterations. The subtle issue of choosing
the matrix subspaces is addressed. Numerical experiments are presented. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|