SIAM Journal on Matrix Analysis and Applications · 2002 · 25 citations · 25 references
Natural SciencesComputer ScienceMathematicsComputational PhysicsOptimizationParallel ComputingApproximation AlgorithmsApproximation MethodsMatrix ComputationNumerical AlgorithmsNumerical AnalysisNumerical Linear AlgebraApproximation By Rational PointsApproximation By Trigonometric PolynomialsPreconditioningPreconditioning TechniquesRational Approximation TheoryRational Function ApproximationSparse Matrix ComputationToeplitz Operators
It is well known that preconditioned conjugate gradient (PCG) methods are widely used to solve ill-conditioned Toeplitz linear systems Tn(f)x=b. In this paper we present a new preconditioning technique for the solution of symmetric Toeplitz systems generated by nonnegative functions f with zeros of even order. More specifically, f is divided by the appropriate trigonometric polynomial g of the smallest degree, with zeros the zeros of f to eliminate its zeros. Using rational approximation we approximate $\sqrt{f/g}$ by $\frac{p}{q}$, $p,q$ trigonometric polynomials and consider $\frac{p^2g}{q^2}$ as a very satisfactory approximation of f. We propose the matrix $M_n=B^{-1}_n(q)B_n(p^2g)B^{-1}_n(q)$, where $B(\cdot)$ denotes the associated band Toeplitz matrix, as a preconditioner whence a good clustering of the spectrum of its preconditioned matrix is obtained. We also show that the proposed technique can be very flexible, a fact that is confirmed by various numerical experiments so that in many cases it constitutes a much more efficient strategy than the existing ones.
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