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Preconditioning of elliptic problems by approximation in the transform domain

Research output: Contribution to journalJournal articlepeer-review

4 Citations (Scopus)

Abstract

Preconditioned conjugate gradient method is applied for solving linear systemsAx=b where the matrixA is the discretization matrix of second-order elliptic operators. In this paper, we consider the construction of the trnasform based preconditioner from the viewpoint of image compression. Given a smooth image, a major portion of the energy is concentrated in the low frequency regions after image transformation. We can view the matrixA as an image and construct the transform based preconditioner by using the low frequency components of the transformed matrix. It is our hope that the smooth coefficients of the given elliptic operator can be approximated well by the low-rank matrix. Numerical results are reported to show the effectiveness of the preconditioning strategy. Some theoretical results about the properties of our proposed preconditioners and the condition number of the preconditioned matrices are discussed.

Original languageEnglish
Pages (from-to)885-900
Number of pages16
JournalBIT Numerical Mathematics
Volume38
Issue number1
DOIs
Publication statusPublished - Dec 1997

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

User-Defined Keywords

  • Transform approximation
  • Image compression
  • Preconditioned conjugate gradient method

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