TITLE:
An Improved Wavelet Based Preconditioner for Sparse Linear Problems
AUTHORS:
Arikera Padmanabha Reddy, Nagendrapp M. Bujurke
KEYWORDS:
Discrete Wavelet Transform, Preconditioners, Sparse Matrices, Krylov Subspace Iterative Methods
JOURNAL NAME:
Applied Mathematics,
Vol.1 No.5,
November
30,
2010
ABSTRACT: In this paper, we present the construction of purely algebraic Daubechies wavelet based preconditioners for Krylov subspace iterative methods to solve linear sparse system of equations. Effective preconditioners are designed with DWTPerMod algorithm by knowing size of the matrix and the order of Daubechies wavelet. A notable feature of this algorithm is that it enables wavelet level to be chosen automatically making it more robust than other wavelet based preconditioners and avoids user choosing a level of transform. We demonstrate the efficiency of these preconditioners by applying them to several matrices from Tim Davis collection of sparse matrices for restarted GMRES.