Band Toeplitz preconditioners for block Toeplitz systems

We consider the solutions of block Toeplitz systems with Toeplitz blocks by the preconditioned conjugate gradient (PCG) method. Here the block Toeplitz matrices are generated by nonnegative functions f(x,y). We use band Toeplitz matrices as preconditioners. The generating functions g(x,y) of the preconditioners are trigonometric polynomials of fixed degree and are determined by minimizing (f − g)/f∞. We prove that the condition number of the preconditioned system is O(1). An a priori bound on the number of iterations for convergence is obtained.     

Band-Toeplitz preconditioners for ill-conditioned Toeplitz systems

BIT Numerical Mathematics - Preconditioning for Toeplitz systems has been an active research area over the past few decades. Along this line of research, circulant preconditioners have been...     

Band-times-circulant preconditioners for non-symmetric Toeplitz systems

BIT Numerical Mathematics - In this paper we study $$ntimes n$$ non-symmetric, real Toeplitz systems of the form $$T_n(f)x = b$$ , where the generating function of the Toeplitz matrix f is known a...     

Circulant preconditioners for discrete ill-posed Toeplitz systems

Circulant preconditioners are commonly used to accelerate the rate of convergence of iterative methods when solving linear systems of equations with a Toeplitz matrix. Block extensions that can be applied when the system has a block Toeplitz matrix with Toeplitz blocks also have been developed. This paper is concerned with preconditioning of linear systems of equations with a symmetric block Toeplitz matrix with symmetric Toeplitz blocks that stem from the discretization of a linear ill-posed problem. The right-hand side of the linear systems represents available data and is assumed to be contaminated by error. These kinds of linear systems arise, e.g., in image deblurring problems. It is important that the preconditioner does not affect the invariant subspace associated with the smallest eigenvalues of the block Toeplitz matrix to avoid severe propagation of the error in the right-hand side. A perturbation result indicates how the dimension of the subspace associated with the smallest eigenvalues should be chosen and allows the determination of a suitable preconditioner when an estimate of the error in the right-hand side is available. This estimate also is used to decide how many iterations to carry out by a minimum residual iterative method. Applications to image restoration are presented.     

Look-ahead Levinson and Schur algorithms for non-Hermitian Toeplitz systems

Summary. We present generalizations of the nonsymmetric Levinson and Schur algorithms for non-Hermitian Toeplitz matrices with some singular or ill-conditioned leading principal submatrices. The underlying recurrences allow us to go from any pair of successive well-conditioned leading principal submatrices to any such pair of larger order. If the look-ahead step size between these pairs is bounded, our generalized Levinson and Schur recurrences require $ operations, and the Schur recurrences can be combined with recursive doubling so that an $ algorithm results. The overhead (in operations and storage) of look-ahead steps is very small. There are various options for applying these algorithms to solving linear systems with Toeplitz matrix. Received July 26, 1993     

Preconditioners for block Toeplitz systems based on circulant preconditioners

We study the numerical solution of a block system T _m,n x=b by preconditioned conjugate gradient methods where T _m,n is an m×m block Toeplitz matrix with n×n Toeplitz blocks. These systems occur in a variety of applications, such as two-dimensional image processing and the discretization of two-dimensional partial differential equations. In this paper, we propose new preconditioners for block systems based on circulant preconditioners. From level-1 circulant preconditioner we construct our first preconditioner q ₁(T _m,n ) which is the sum of a block Toeplitz matrix with Toeplitz blocks and a sparse matrix with Toeplitz blocks. By setting selected entries of the inverse of level-2 circulant preconditioner to zero, we get our preconditioner q ₂(T _m,n ) which is a (band) block Toeplitz matrix with (band) Toeplitz blocks. Numerical results show that our preconditioners are more efficient than circulant preconditioners.     

Circulant and skew-circulant preconditioners for skew-hermitian type Toeplitz systems

We study the solutions of Toeplitz systemsA _n x=b by the preconditioned conjugate gradient method. Then ×n matrixA _n is of the forma ₀ I+H _n wherea ₀ is a real number,I is the identity matrix andH _n is a skew-Hermitian Toeplitz matrix. Such matrices often appear in solving discretized hyperbolic differential equations. The preconditioners we considered here are the circulant matrixC _n and the skew-circulant matrixS _n whereA _n =1/2(C _n +S _n ). The convergence rate of the iterative method depends on the distribution of the singular values of the matricesC ^–1 _n A_n andS ^–1 _n A _n . For Toeplitz matricesA _n with entries which are Fourier coefficients of functions in the Wiener class, we show the invertibility ofC _n andS _n and prove that the singular values ofC ^–1 _n A _n andS ^–1 _n A _n are clustered around 1 for largen. Hence, if the conjugate gradient method is applied to solve the preconditioned systems, we expect fast convergence.     

Hartley preconditioners for Toeplitz systems generated by positive continuous functions

In this paper, we consider the solution ofn-by-n symmetric positive definite Toeplitz systemsT _n x=b by the preconditioned conjugate gradient (PCG) method. The preconditionerM _n is defined to be the minimizer of T _n –B _{n F} over allB _n H _n whereH _n is the Hartley algebra. We show that if the generating functionf ofT _n is a positive 2-periodic continuous even function, then the spectrum of the preconditioned systemM _n ^–1 T _n will be clustered around 1. Thus, if the PCG method is applied to solve the preconditioned system, the convergence rate will be superlinear.     

Approximate inverse-free preconditioners for Toeplitz matrices

In this paper, we propose approximate inverse-free preconditioners for solving Toeplitz systems. The preconditioners are constructed based on the famous Gohberg-Semencul formula. We show that if a Toeplitz matrix is generated by a positive bounded function and its entries enjoys the off-diagonal decay property, then the eigenvalues of the preconditioned matrix are clustered around one. Experimental results show that the proposed preconditioners are superior to other existing preconditioners in the literature.     

The best circulant preconditioners for Hermitian Toeplitz systems II: The multiple-zero case

Summary. In [10,14], circulant-type preconditioners have been proposed for ill-conditioned Hermitian Toeplitz systems that are generated by nonnegative continuous functions with a zero of even order. The proposed circulant preconditioners can be constructed without requiring explicit knowledge of the generating functions. It was shown that the spectra of the preconditioned matrices are uniformly bounded except for a fixed number of outliers and that all eigenvalues are uniformly bounded away from zero. Therefore the conjugate gradient method converges linearly when applied to solving the circulant preconditioned systems. In [10,14], it was claimed that this result can be the case where the generating functions have multiple zeros. The main aim of this paper is to give a complete convergence proof of the method in [10,14] for this class of generating functions. Received October 19, 1999 / Revised version received May 2, 2001 / Published online October 17, 2001     

Optimal, quasi-optimal and superlinear band-Toeplitz preconditioners for asymptotically ill-conditioned positive definite Toeplitz systems

In this paper we are concerned with the solution of Hermitian Toeplitz systems with nonnegative generating functions . The preconditioned conjugate gradient (PCG) method with the well-known circulant preconditioners fails in the case where has zeros. In this paper we consider as preconditioners band-Toeplitz matrices generated by trigonometric polynomials of fixed degree . We use different strategies of approximation of to devise a polynomial which has some analytical properties of , is easily computable and is such that the corresponding preconditioned system has a condition number bounded by a constant independent of . For each strategy we analyze the cost per iteration and the number of iterations required for the convergence within a preassigned accuracy. We obtain different estimates of for which the total cost of the proposed PCG methods is optimal and the related rates of convergence are superlinear. Finally, for the most economical strategy, we perform various numerical experiments which fully confirm the effectiveness of approximation theory tools in the solution of this kind of linear algebra problems.

     

BTTB preconditioners for BTTB systems

In this paper, we consider solving the BTTB system \({\cal T}_{m,n}[f] {\bf{x}} = {\bf{b}}\) by the preconditioned conjugate gradient (PCG) method, where \({\cal T}_{m,n}[f]\) denotes the m × m block Toeplitz matrix with n × n Toeplitz blocks (BTTB) generated by a (2π, 2π)-periodic continuous function f(x, y). We propose using the BTTB matrix \({\cal T}_{m,n}[1/f]\) to precondition the BTTB system and prove that only O(m)?+?O(n) eigenvalues of the preconditioned matrix \({\cal T}_{m,n}[1/f] {\cal T}_{m,n}[f]\) are not around 1 under the condition that f(x, y)?>?0. We then approximate 1/f(x, y) by a bivariate trigonometric polynomial, which can be obtained in O(m n log(m n)) operations by using the fast Fourier transform technique. Numerical results show that our BTTB preconditioner is more efficient than block circulant preconditioners.     

Several splittings for non-Hermitian linear systems

For large sparse non-Hermitian positive definite system of linear equations,we present several variants of the Hermitian and skew-Hermitian splitting(HSS)about the coefficient matrix and establish correspondingly several HSS-based iterative schemes.Theoretical analyses show that these methods are convergent unconditionally to the exact solution of the referred system of linear equations,and they may show advantages on problems that the HSS method is ineffiective.     

Updating preconditioners for permuted non-symmetric linear systems

We consider the solution of a sequence of nonsymmetric linear systems arising from a supersonic model problem by exploiting triangular preconditioner updates. In addition, we demonstrate how the power of the updates can be enhanced by permuting the entire sequence beforehand with a physically motivated reordering of unknowns. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Some preconditioners for systems of linear inequalities

We show that a combination of two simple preprocessing steps would generally improve the conditioning of a homogeneous system of linear inequalities. Our approach is based on a comparison among three different but related notions of conditioning for linear inequalities.     

Strang-type preconditioners for systems of LMF-based ODE codes

We consider the solution of ordinary differential equations(ODEs) using boundary value methods. These methods require thesolution of one or more unsymmetric, large and sparse linearsystems. The GMRES method with the Strang-type block-circulantpreconditioner is proposed for solving these linear systems.We show that if an A_k1,k2 -stable boundary value method is usedfor an m-by-m system of ODEs, then our preconditioners are invertibleand all the eigenvalues of the preconditioned systems are 1except for at most 2m(k₁ + k₂) outliers. It follows that whenthe GMRES method is applied to solving the preconditioned systems,the method will converge in at most 2m(k₁ + k₂) + 1 iterations.Numerical results are given to illustrate the effectivenessof our methods. Received 8 October 1999. Accepted 30 May 2000.     

Block band Toeplitz preconditioners derived from generating function approximations: analysis and applications

We are concerned with the study and the design of optimal preconditioners for ill-conditioned Toeplitz systems that arise from a priori known real-valued nonnegative generating functions f(x,y) having roots of even multiplicities. Our preconditioned matrix is constructed by using a trigonometric polynomial θ(x,y) obtained from Fourier/kernel approximations or from the use of a proper interpolation scheme. Both of the above techniques produce a trigonometric polynomial θ(x,y) which approximates the generating function f(x,y), and hence the preconditioned matrix is forced to have clustered spectrum. As θ(x,y) is chosen to be a trigonometric polynomial, the preconditioner is a block band Toeplitz matrix with Toeplitz blocks, and therefore its inversion does not increase the total complexity of the PCG method. Preconditioning by block Toeplitz matrices has been treated in the literature in several papers. We compare our method with their results and we show the efficiency of our proposal through various numerical experiments.This research was co-funded by the European Union in the framework of the program “Pythagoras I” of the “Operational Program for Education and Initial Vocational Training” of the 3rd Community Support Framework of the Hellenic Ministry of Education, funded by national sources (25%) and by the European Social Fund - ESF (75%). The work of the second and of the third author was partially supported by MIUR (Italian Ministry of University and Research), grant number 2004015437.     

Kronecker product approximation preconditioners for convection–diffusion model problems

We consider the iterative solution of linear systems arising from four convection–diffusion model problems: scalar convection–diffusion problem, Stokes problem, Oseen problem and Navier–Stokes problem. We design preconditioners for these model problems that are based on Kronecker product approximations (KPAs). For this we first identify explicit Kronecker product structure of the coefficient matrices, in particular for the convection term. For the latter three model cases, the coefficient matrices have a 2 × 2 block structure, where each block is a Kronecker product or a summation of several Kronecker products. We then use this structure to design a block diagonal preconditioner, a block triangular preconditioner and a constraint preconditioner. Numerical experiments show the efficiency of the three KPA preconditioners, and in particular of the constraint preconditioner that usually outperforms the other two. This can be explained by the relationship that exists between these three preconditioners: the constraint preconditioner can be regarded as a modification of the block triangular preconditioner, which at its turn is a modification of the block diagonal preconditioner based on the cell Reynolds number. Copyright © 2009 John Wiley & Sons, Ltd.