Computations with quasiseparable polynomials and matrices
Theoretical Computer Science
Applications of FFT and structured matrices
Algorithms and theory of computation handbook
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In this paper we use a displacement structure approach to design a class of new preconditioners for the conjugate gradient method applied to the solution of large Toeplitz linear equations. Explicit formulas are suggested for the G.Strang-type and for the T.Chan-type preconditioners belonging to any of eight classes of matrices diagonalized by the corresponding discrete cosine or sine transforms. Under the standard Wiener class assumption the clustering property is established for all of these preconditioners, guaranteeing rapid convergence of the preconditioned conjugate gradient method. All the computations related to the new preconditioners can be done in real arithmetic, and to fully exploit this advantageous property one has to suggest a fast real-arithmetic algorithm for multiplication of a Toeplitz matrix by a vector. It turns out that the obtained formulas for the Strang-type preconditioners allow a number of representations for Toeplitz matrices leading to a wide variety of real-arithmetic multiplication algorithms based on any of eight discrete cosine or sine transforms.Recently, transformations of Toeplitz matrices to Vandermonde-like or Cauchy-like matrices have been found to be useful in developing accurate direct methods for Toeplitz linear equations. In this paper we suggest further extending the range of the transformation approach by exploring it for iterative methods; this technique allowed us to reduce the complexity of each iteration of the preconditioned conjugate gradient method. The results of this paper were announced in [T. Kailath and V. Olshevsky, Calcolo, 33 (1996), pp. 191--208].