An Improved Wavelet Based Preconditioner for Sparse Linear Problems
Arikera Padmanabha Reddy, Nagendrapp M. Bujurke
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DOI: 10.4236/am.2010.15049   PDF    HTML     3,947 Downloads   7,959 Views   Citations

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.

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Reddy, A. and Bujurke, N. (2010) An Improved Wavelet Based Preconditioner for Sparse Linear Problems. Applied Mathematics, 1, 370-376. doi: 10.4236/am.2010.15049.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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