Preconditioned Lanczos Methods for the Minimum Eigenvalue of a Symmetric Positive Definite Toeplitz Matrix

Michael K. Ng*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

9 Citations (Scopus)

Abstract

In this paper, we apply the preconditioned Lanczos (PL) method to compute the minimum eigenvalue of a symmetric positive definite Toeplitz matrix. The sine transform-based preconditioner is used to speed up the convergence rate of the PL method. The resulting method involves only Toeplitz and sine transform matrix-vector multiplications and hence can be computed efficiently by fast transform algorithms. We show that if the symmetric Toeplitz matrix is generated by a positive 2π-periodic even continuous function, then the PL method will converge sufficiently fast. Numerical results including Toeplitz and non-Toeplitz matrices are reported to illustrate the effectiveness of the method.

Original languageEnglish
Pages (from-to)1973-1986
Number of pages14
JournalSIAM Journal on Scientific Computing
Volume21
Issue number6
DOIs
Publication statusPublished - Jan 2000

Scopus Subject Areas

  • Computational Mathematics
  • Applied Mathematics

User-Defined Keywords

  • Toeplitz matrix
  • sine transform matrix
  • fast sine transform
  • preconditioning
  • Lanczos method

Fingerprint

Dive into the research topics of 'Preconditioned Lanczos Methods for the Minimum Eigenvalue of a Symmetric Positive Definite Toeplitz Matrix'. Together they form a unique fingerprint.

Cite this