1996
DOI: 10.1090/s0025-5718-96-00682-5
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Which circulant preconditioner is better?

Abstract: Abstract. The eigenvalue clustering of matrices S −1 n An and C −1 n An is experimentally studied, where An, Sn and Cn respectively are Toeplitz matrices, Strang, and optimal circulant preconditioners generated by the Fourier expansion of a function f (x). Some illustrations are given to show how the clustering depends on the smoothness of f (x) and which preconditioner is preferable. An original technique for experimental exploration of the clustering rate is presented. This technique is based on the bisectio… Show more

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Cited by 41 publications
(20 citation statements)
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“…In the case where there is strong convergence (strong or proper clustering in the terminology used in [65]) and the function f is strictly positive, we have a superlinear convergence of the related PCG methods having {P Un (A n (f ))} n as preconditioner, but we may have a sublinear behaviour when the weak convergence (weak or general clustering [65]) case occurs [60,24].…”
Section: Definition 32mentioning
confidence: 99%
“…In the case where there is strong convergence (strong or proper clustering in the terminology used in [65]) and the function f is strictly positive, we have a superlinear convergence of the related PCG methods having {P Un (A n (f ))} n as preconditioner, but we may have a sublinear behaviour when the weak convergence (weak or general clustering [65]) case occurs [60,24].…”
Section: Definition 32mentioning
confidence: 99%
“…In fact, it is known that if the spectrum of a Hermitian matrix A exhibits a proper cluster at 1 as the dimension n grows, that is if all its eigenvalues lie in a fixed neighbourhood of 1 except a finite number of outliers independent on n, then the conjugate gradient method applied to the linear system Ax ¼ b converges superlinearly [1,19] (see also [22]). …”
Section: Numerical Resultsmentioning
confidence: 99%
“…From Table 6.4 we see that the superoptimal preconditioner is not as effective as the optimal or Strang preconditioners. This may be related to the lack of satisfaction of our theory, but it is also known in the symmetric case that when A n is ill conditioned the superoptimal preconditioner may preserve small eigenvalues that hamper convergence [15,44]. The condition numbers of the preconditioned matrices are given in Table 6.5.…”
Section: Extension To Block Matricesmentioning
confidence: 99%