Convergence of Rump's method for inverting arbitrarily ill-conditioned matrices

  • Authors:
  • Shin'ichi Oishi;Kunio Tanabe;Takeshi Ogita;Siegfried M. Rump

  • Affiliations:
  • Faculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Tokyo 169-8555, Japan and CREST, Japan Science and Technology Agency, Japan;Faculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Tokyo 169-8555, Japan;CREST, Japan Science and Technology Agency, Japan and Faculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Tokyo 169-8555, Japan;Institute for Reliable Computing, Hamburg University of Technology, Schwarzenbergstr. 95, Hamburg 21071, Germany and Faculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Tokyo 169-8 ...

  • Venue:
  • Journal of Computational and Applied Mathematics
  • Year:
  • 2007

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Abstract

In this paper, the problem of inverting regular matrices with arbitrarily large condition number is treated in double precision defined by IEEE 754 floating point standard. In about 1984, Rump derived a method for inverting arbitrarily ill-conditioned matrices. The method requires the possibility to calculate a dot product in higher precision. Rump's method is of theoretical interest. Rump made it clear that inverting an arbitrarily ill-conditioned matrix in single or double precision does not produce meaningless numbers, but contains a lot of information in it. Rump's method uses such inverses as preconditioners. Numerical experiments exhibit that Rump's method converges rapidly for various matrices with large condition numbers. Why Rump's method is so efficient for inverting arbitrarily ill-conditioned matrices is a little mysterious. Thus, to prove its convergence is an interesting problem in numerical error analysis. In this article, a convergence theorem is presented for a variant of Rump's method.