On solving the Ill-conditioned system Ax = b: General-purpose conditioners obtained from the boundary-collocation solution of the laplace equation, using trefftz expansionswith multiple length scales

Chein Shan Liu, Weichung Yeih, Satya N. Atluri

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Abstract

Here we develop a general purpose pre/post conditioner T, to solve an ill-posed system of linear equations, Ax = b. The conditioner T is obtained in the course of the solution of the Laplace equation, through a boundary-collocation Trefftz method, leading to: Ty = x, where y is the vector of coefficients in the Trefftz expansion, and x is the boundary data at the discrete points on a unit circle. We show that the quality of the conditioner T is greatly enhanced by using multiple characteristic lengths (Multiple Length Scales) in the Trefftz expansion. We further show that T can be multiplicatively decomposed into a dilation TD and a rotation TR. For an odd-ordered A, we develop four conditioners based on the solution of the Laplace equation for Dirichlet boundary conditions, while for an even-ordered A we develop four conditioners employing the Neumann boundary conditions. All these conditioners are well-behaved and easily invertible. Several examples involving ill-conditioned A, such as the Hilbert matrices, those arising from the Method of Fundamental Solutions, those arising from very-high order polynomial interpolations, and those resulting from the solution of the first-kind Fredholm integral equations, are presented. The results demonstrate that the presently proposed conditioners result in very high computational efficiency and accuracy, when Ax = b is highly ill-conditioned, and b is noisy.

Original languageEnglish
Pages (from-to)281-311
Number of pages31
JournalCMES - Computer Modeling in Engineering and Sciences
Volume44
Issue number3
StatePublished - Dec 1 2009

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Keywords

  • Dilation matrix
  • Ill-posed linear equations
  • Multi-scale trefftz method (MSTM)
  • Multi-scale trefftz-collocation laplacian conditioner (MSTCLC)
  • Rotation matrix
  • Transformation matrix

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