Recursive-Based PCG Methods for Toeplitz Systems with Nonnegative Generating Functions

  • Authors:
  • Michael K. Ng;Hai-Wei Sun;Xiao-Qing Jin

  • Affiliations:
  • -;-;-

  • Venue:
  • SIAM Journal on Scientific Computing
  • Year:
  • 2002

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Abstract

In this paper, we consider the solutions of symmetric positive definite, but ill-conditioned, Toeplitz systems An x = b. Here we propose to solve the system by the recursive-based preconditioned conjugate gradient method. The idea is to use the inverse of Am (the principal submatrix of An with the Gohberg--Semencul formula as a preconditioner for An. The inverse of Am can be generated recursively by using the formula until m is small enough. The construction of the preconditioners requires only the entries of An and does not require the explicit knowledge of the generating function f of An. We show that if f is a nonnegative, bounded, and piecewise continuous even function with a finite number of zeros of even order, the spectra of the preconditioned matrices are uniformly bounded except for a fixed number of outliers. Hence the conjugate gradient method, when applied to solving the preconditioned system, converges very quickly. Numerical results are included to illustrate the effectiveness of our approach.