On the inverses of a class of toeplitz matrices of band width five

For a symmetric positive definite Toeplitz matrix of band width five and order n, those regions where the elements of the inverse alternative in sign are determined.     

On the infinity norm of the inverse of a class of toeplitz matrices of band width five

A useful theorem for precisely bounding the infinity norm of the inverse of a five-diagonal symmetric positive definite Toeplitz matrix is obtained.     

The inverses of Toeplitz band matrices

The elements of the inverse of a Toeplitz band matrix are given in terms ofthe solution of a difference equation. The expression for these elements is a quotient of determinants whose orders depend the number of nonzero superdiagonals but not on the order of the matrix. Thus, the formulae are particularly simple for lower triangular and lower Hessenberg Toeplitz matrices. When the number of nonzero superdiagonals is small, sufficient conditions on the solution of the abovementioned difference equation can be given to ensure that the inverse matrix is positive. If the inverse is positive, the row sums can be expressed in terms of the solution of the difference equation.     

On the reconstruction of Toeplitz matrix inverses from columns

In this paper we discuss the problem whether and how the inverse of a Toeplitz matrix can be recovered from some of its columns or parts of columns under the requirement that only 2n−1 parameters are involved. The results generalize and strengthen earlier findings by Trench, Gohberg, Semencul, Krupnik, Ben-Artzi, Shalom, Labahn, Rodman and others. Special attention is paid to symmetric, skewsymmetric and hermitian Toeplitz matrix inverses and the question whether such a matrix can be retrieved from a single column.     

Symmetric centrosymmetric matrix–vector multiplication

We present a method for the multiplication of an arbitrary vector by a symmetric centrosymmetric matrix, requiring floating-point operations, rather than the 2n² operations needed in the case of an arbitrary matrix. Combining this method with Trench's algorithm for Toeplitz matrix inversion yields a method for solving Toeplitz systems with the same complexity as Levinson's algorithm.     

A fast algorithm for computing the smallest eigenvalue of a symmetric positive‐definite Toeplitz matrix

Recent progress in signal processing and estimation has generated considerable interest in the problem of computing the smallest eigenvalue of a symmetric positive‐definite (SPD) Toeplitz matrix. An algorithm for computing upper and lower bounds to the smallest eigenvalue of a SPD Toeplitz matrix has been recently derived (Linear Algebra Appl. 2007; DOI: 10.1016/j.laa.2007.05.008 ). The algorithm relies on the computation of the R factor of the QR factorization of the Toeplitz matrix and the inverse of R. The simultaneous computation of R and R^?1 is efficiently accomplished by the generalized Schur algorithm. In this paper, exploiting the properties of the latter algorithm, a numerical method to compute the smallest eigenvalue and the corresponding eigenvector of SPD Toeplitz matrices in an accurate way is proposed. Copyright © 2008 John Wiley & Sons, Ltd.     

A derivation of the Levinson algorithm for solving linear systems with symmetric positive definite Toeplitz matrix

Based on an orthogonalization technique, published earlier in this journal, a derivation is given of the Levinson algorithm for solving systems with a symmetric positive definite Toeplitz matrix.     

Symmetric Gaussian elimination for cauchy-type matrices with application to positive definite Toeplitz matrices

The problem of solving linear equations with a Toeplitz matrix appears in many applications. Often is positive definite but ill-conditioned with many small eigenvalues. In this case fast and superfast algorithms may show a very poor behavior or even break down. In recent papers the transformation of a Toeplitz matrix into a Cauchy-type matrix is proposed. The resulting new linear equations can be solved in operations using standard pivoting strategies which leads to very stable fast methods also for ill-conditioned systems. The basic tool is the formulation of Gaussian elimination for matrices with low displacement rank. In this paper, we will transform a Hermitian Toeplitz matrix into a Cauchy-type matrix by applying the Fourier transform. We will prove some useful properties of and formulate a symmetric Gaussian elimination algorithm for positive definite . Using the symmetry and persymmetry of we can reduce the total costs of this algorithm compared with unsymmetric Gaussian elimination. For complex Hermitian , the complexity of the new algorithm is then nearly the same as for the Schur algorithm. Furthermore, it is possible to include some strategies for ill-conditioned positive definite matrices that are well-known in optimization. Numerical examples show that this new algorithm is fast and reliable. Received March 24, 1995 / Revised version received December 13, 1995     

SQP algorithms for solving Toeplitz matrix approximation problem

Given an n × n matrix F, we find the nearest symmetric positive semi‐definite Toeplitz matrix T to F. The problem is formulated as a non‐linear minimization problem with positive semi‐definite Toeplitz matrix as constraints. Then a computational framework is given. An algorithm with rapid convergence is obtained by l₁ Sequential Quadratic Programming (SQP) method. Copyright © 2002 John Wiley & Sons, Ltd.     

Conservative solution of the Fokker–Planck equation for stochastic chemical reactions

In this paper we discuss multigrid methods for ill-conditioned symmetric positive definite block Toeplitz matrices. Our block Toeplitz systems are general in the sense that the individual blocks are not necessarily Toeplitz, but we restrict our attention to blocks of small size. We investigate how transfer operators for prolongation and restriction have to be chosen such that our multigrid algorithms converge quickly. We point out why these transfer operators can be understood as block matrices as well and how they relate to the zeroes of the generating matrix function. We explain how our new algorithms can also be combined efficiently with the use of a natural coarse grid operator. We clearly identify a class of ill-conditioned block Toeplitz matrices for which our algorithmic ideas are suitable. In the final section we present an outlook to well-conditioned block Toeplitz systems and to problems of vector Laplace type. In the latter case the small size blocks can be interpreted as degrees of freedom associated with a node. A large number of numerical experiments throughout the article confirms convincingly that our multigrid solvers lead to optimal order convergence. AMS subject classification (2000) 65N55, 65F10     

关于实方阵的几个问题

本文讨论如下内容：１．把有关对称正定（半正定）的一些性质推广到广义正定（半正定）。２．给定ｘ∈Ｒｍ×ｍ，∧为对角阵，求ＡＸ＝ｘ∧在对称半正定矩阵类中解存在的充要条件及一般形式，并讨论了对任意给定的对称正定（半正定）矩阵Ａ，在上述解的集合中求得Ａ，使得     

SINE TRANSFORM MATRIX FOR SOLVING TOEPLITZ MATRIX PROBLEMS

1. IntroductionStrang[1] first studied the use of circulallt matrices C for solving systems of linear eqllationsTi x = b witha symmetric positive definite Toeplitz matrix.Numerous authors such as T.Chan[2],R.Chan,etc.[3],[4],[5], Tyrtyshnikov[6], Huckle[7] and T.Ku and C.Kuo[8] proposed differentfamilies of circulallt / skew- circulant precondit ioners.Appling the preconditioned conjugate gradient algorithm(PCGA) to solve the systems Ti x -b, we must find a preconditioner P such that P…     

Order invariant properties of some matrices

Certain important Toeplitz and composite Toeplitz matrices have order invariant properties. A class of matrices is defined, and a notation for sign patterns of vector and matrix elements is developed which enables some order invariant properties of the matrices to be described. Several examples are given to show how these ideas apply to some important matrices, including those commonly arising from the numerical solution of elliptic partial differential equations. The following information about the inverse of these matrices is obtained: the signs of the elements, the row in which the maximum row sum occurs, and the signs of the elements of the eigenvector corresponding to its dominant eigenvalue.     

On inverse eigenvalue problems for block Toeplitz matrices with Toeplitz blocks

We propose an algorithm for solving the inverse eigenvalue problem for real symmetric block Toeplitz matrices with symmetric Toeplitz blocks. It is based upon an algorithm which has been used before by others to solve the inverse eigenvalue problem for general real symmetric matrices and also for Toeplitz matrices. First we expose the structure of the eigenvectors of the so-called generalized centrosymmetric matrices. Then we explore the properties of the eigenvectors to derive an efficient algorithm that is able to deliver a matrix with the required structure and spectrum. We have implemented our ideas in a Matlab code. Numerical results produced with this code are included.     

Positive Definite Toeplitz Completions

The problem of completing a partially prescribed Toeplitz matrixto a positive definite Toeplitz matrix is considered. The mainresult is a characterization of the patterns of specified entriesthat guarantee the existence of a positive definite Toeplitzcompletion of a partial positive definite Toeplitz matrix. Thischaracterization resolves affirmatively a conjecture of C. R.Johnson and L. Rodman.     

Analysis of a novel preconditioner for a class of p‐level lower rank extracted systems

This paper proposes and studies the performance of a preconditioner suitable for solving a class of symmetric positive definite systems, Âx=b, which we call p‐level lower rank extracted systems (p‐level LRES), by the preconditioned conjugate gradient method. The study of these systems is motivated by the numerical approximation of integral equations with convolution kernels defined on arbitrary p‐dimensional domains. This is in contrast to p‐level Toeplitz systems which only apply to rectangular domains. The coefficient matrix, Â, is a principal submatrix of a p‐level Toeplitz matrix, A, and the preconditioner for the preconditioned conjugate gradient algorithm is provided in terms of the inverse of a p‐level circulant matrix constructed from the elements of A. The preconditioner is shown to yield clustering in the spectrum of the preconditioned matrix which leads to a substantial reduction in the computational cost of solving LRE systems. Copyright © 2006 John Wiley & Sons, Ltd.     

Numerical approximation of the product of the square root of a matrix with a vector

Given an n×n symmetric positive definite matrix A and a vector , two numerical methods for approximating are developed, analyzed, and computationally tested. The first method applies a Newton iteration to a specific nonlinear system to approximate while the second method applies a step-control method to numerically solve a specific initial-value problem to approximate . Assuming that A is first reduced to tridiagonal form, the first method requires O(n²) operations per iteration while the second method requires O(n) operations per iteration. In contrast, numerical methods that first approximate A^1/2 and then compute generally require O(n³) operations per iteration.     

On functions which preserve the class of Stieltjes matrices

A positive definite symmetric matrix is called a Stieltjes matrix provided that all its off diagonal elements are nonpositive. We characterize functions which preserve the class of Stieltjes matrices.     

Bounds on the diagonal elements of a unitary matrix

It was shown by A. Horn that the diagonal elements of a unitary n×n matrix satisfy a set of linear inequalities (Theorem I). We give a simple proof of this result, and we show that the diagonal elements satisfy additional linear inequalities (Theorem II) if the matrix is also symmetric.     

Weak stability for matrices

An n×n complex matrix A is called weak stable if there exists a matrix W such that W+W^* is positive definite and such that AW+W^*A^* is positive definite. In this note several characterizations for weak stability of a matrix are given, and conditions (on A) allowing W to be a diagonal matrix are also considered. A consequence of our results here is a characterization for nonsingular M-matrices.