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

Shin'ichi Oishi*, Kunio Tanabe, Takeshi Ogita, Siegfried M. Rump

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)533-544
Number of pages12
JournalJournal of Computational and Applied Mathematics
Issue number1
Publication statusPublished - 2007 Aug 1


  • Accurate dot product
  • Ill-conditioned matrix
  • Matrix inversion
  • Precondition

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics


Dive into the research topics of 'Convergence of Rump's method for inverting arbitrarily ill-conditioned matrices'. Together they form a unique fingerprint.

Cite this