关于(R,r)-循环分块矩阵求逆与相乘的一种快速算法

利用矩阵分块逐次降阶的方法和快速富里叶变换(FFT),给出了mn阶(R,r)-循环分块矩阵求逆与相乘的一种快速算法,证明了其计算复杂性为O(mnlog2mn).     

三对角与五对角Toeplitz矩阵求逆的算法

提出了一种求三对角与五对角Toeplitz矩阵逆的快速算法,其思想为先将Toeplitz矩阵扩展为循环矩阵,再快速求循环矩阵的逆,进而运用恰当矩阵分块求原Toeplitz矩阵的逆的算法.算法稳定性较好且复杂度较低.数值例子显示了算法的有效性和稳定性,并指出了算法的适用范围.     

关于三角形Toeplitz系统的复杂性

目前,已有结果表明,作两个n阶上(或下)三角形T矩阵的乘积以及做n阶三角形T矩阵乘n维列向量的算术运算次数,均不超过O(nlog_2n);而求n阶三角形T矩阵的逆,其工作量则不超过O(nlog_2~2n). 本文给出三角形T矩阵求逆与求解三角形Toeplitz线性方程组的快速算法.该算     

mn阶分块(R,r)-循环矩阵相乘和特征值计算的快速算法

本文利用快速富里叶变换（FFT），给出了mn阶分块（R，r)－循环矩阵相乘和特征值计算的快速算法，其时间复杂性均为O（mnlog2mn）。     

Toeplitz型矩阵的逆矩阵的快速三角分解算法

针对有关“型”矩阵的三角分解问题 ,提出了一种 Toeplitz型矩阵的逆矩阵的快速三角分解算法 .首先假设给定 n阶非奇异矩阵 A,利用一组线性方程组的解 ,得到 A- 1的一个递推关系式 ,进而利用该关系式得到 A- 1的一种三角分解表达式 ,然后从 Toeplitz型矩阵的特殊结构出发 ,利用上述定理的结论 ,给出了Toeplitz型矩阵的逆矩阵的一种快速三角分解算法 ,算法所需运算量为 O( mn2 ) .最后 ,数值计算表明该算法的可靠性 .     

分块带状矩阵的逆

1引言如果分块矩阵A=(A_(ij))_(n×n)满足A_(ij)=O(j-i＞p且i-j＞q),其中A_(ij)为m阶矩阵,则称A为(p,q)-分块带状矩阵．分块带状矩阵在一些实际问题中经常出现,例如在量子场论中用途很广的非线性Schr(?)dinger方程的差分离散问题,解热传导问题等,都会遇到分块带状矩阵．常见的分块三对角矩阵,分块五对角矩阵都是特殊的分块带状矩阵．采用通常的方法求解分块带状矩阵的逆矩阵时,需要进行O(n~3)次m阶矩阵的运算．本文首先将分块带状矩阵扩充成可逆的分块上(下)三角矩阵,利用其逆矩阵导出了分块带状矩阵的逆矩阵表达式；进而利用所得到的公式分别推导了分块三对角矩阵及分块五对角矩阵的逆矩阵的快速算法,所需运算量为O(n~2)次m阶矩阵的运算．本文的结果扩充了文[1]等关于分块三对角阵求逆的相关结果．     

求Toeplitz矩阵各阶主子式和特征值的O(n~2)算法

形如T~(n)=(T_(ij)~(n))_(n×n),T_(ij)~(n)=t_(i-j),i,j=1～n的n阶矩阵称为Toeplitz矩阵。 Toeplitz矩阵(简称T矩阵)是一类很重要的特殊矩阵,地震预报、天气预测、石油勘探等许多应用领域的数学模型中常常遇到T型矩阵,因此研究其快速算法具有很大的实用价值。1964年,W.F.Trench在对称正定的条件下给出了T矩阵求逆的O(n~2)算法。1969年,S.Zohar进一步讨论了Trench的算法,主要工作是对推导的简化以及把对称正定的条件减弱为强非奇(即各阶主子式全不为零),算法的主要思想请参阅文[1]或[2]。     

r-对称循环矩阵及逆矩阵三角分解的快速算法

根据r-对称循环矩阵的特殊结构给出了求这类矩阵本身及其逆矩阵三角分解的快速算法,算法的运算量均为O(n2),一般矩阵及逆矩阵三角分解的运算量均为O(n3).     

求鳞状因子循环矩阵的逆阵及广义逆阵的快速付氏变换法

借助快速付立叶变换(FFT),本文给出一种求n阶鳞状因子循环矩阵的逆阵、自反g-逆、群逆、Moore-Penrose逆的快速算法,该算法的计算复杂性为O(nlog2n),最后给出的两个数值算例表明了该算法的有效性.     

两类循环分块矩阵及其有关算法

本文利用多项式矩阵最大右公因式，给出R-循环分块矩阵的和对称R-循环分块矩阵非奇异以及线性方程组反问题有唯一解的充要条件，进而得到它们求逆、线性方程组唯一解、线性方程组在循环分块矩阵中的反总问题求唯一解的算法。     

块对偶Toeplitz算子的乘积

本文刻画了向量值Bergman空间上块对偶Toeplitz算子有界性和紧性,给出了块对偶Toeplitz算子的乘积是块对偶Toeplitz算子的充要条件.     

Block toeplitz products of block toeplitz matrices

Necessary and sufficient conditions for the product of two block Toeplitz matrices to be block Toeplitz are obtained. In the special case of two Toeplitz matrices, the conditions simplify considerably and, when combined with known necessary and sufficient conditions for a nonsingular Toeplitz matrix to have a Toeplitz inverse, provide a simple characterization of the additional matrix structure required by a subclass of Toeplitz matrices in order for it to be closed with respect to both inversion and multiplication.     

块Toeplitz方程组的快速块Gauss-Seidel迭代算法

本文研究块Toeplitz方程组的块Gauss-Seidel迭代算法。我们首先讨论了块三角Toeplitz矩阵的一些性质,然后给出了求解块三角Toeplitz矩阵逆的快速算法,由此而得到了求解块Toeplitz方程组的快速块Gauss-Seidel迭代算法,最后证明了当系数矩阵为对称正定和H-矩阵时该方法都收敛,数值例子验证了方法的收敛性。     

QR factorization of Toeplitz matrices

Summary This paper presents a new algorithm for computing theQR factorization of anm×n Toeplitz matrix inO(mn) operations. The algorithm exploits the procedure for the rank-1 modification and the fact that both principal (m–1)×(n–1) submatrices of the Toeplitz matrix are identical. An efficient parallel implementation of the algorithm is possible.     

A direct method to solve block banded block Toeplitz systems with non-banded Toeplitz blocks

A fast solution algorithm is proposed for solving block banded block Toeplitz systems with non-banded Toeplitz blocks. The algorithm constructs the circulant transformation of a given Toeplitz system and then by means of the Sherman-Morrison-Woodbury formula transforms its inverse to an inverse of the original matrix. The block circulant matrix with Toeplitz blocks is converted to a block diagonal matrix with Toeplitz blocks, and the resulting Toeplitz systems are solved by means of a fast Toeplitz solver.The computational complexity in the case one uses fast Toeplitz solvers is equal to ξ(m,n,k)=O(mn³)+O(k³n³) flops, there are m block rows and m block columns in the matrix, n is the order of blocks, 2k+1 is the bandwidth. The validity of the approach is illustrated by numerical experiments.     

A gap between hyponormality and subnormality for block Toeplitz operators

This paper concerns a gap between hyponormality and subnormality for block Toeplitz operators. We show that there is no gap between 2-hyponormality and subnormality for a certain class of trigonometric block Toeplitz operators (e.g., its co-analytic outer coefficient is invertible). In addition we consider the extremal cases for the hyponormality of trigonometric block Toeplitz operators: in this case, hyponormality and normality coincide.     

广义块Toeplitz特征值问题的基于sine变换的预处理子

在求块Toeplitz矩阵束（Amn，Bmn）特征值的Lanczos过程中，通过对移位块Toepltz矩阵Amn-ρBmn进行基于sine变换的块预处理，从而改进了位移块Toeplitz矩阵的谱分布，加速了Lanczos过程的收敛速度．该块预处理方法能通过快速算法有效快速执行．本文证明了预处理后Lanczos过程收敛迅速，并通过实验证明该算法求解大规模矩阵问题尤其有效．     

On the Toeplitz embedding of an arbitrary matrix

It has been shown by Delosme and Morf that an arbitrary block matrix can be embedded into a block Toeplitz matrix; the dimension of this embedding depends on the complexity of the matrix structure compared to the block Toeplitz structure. Due to the special form of the embedding matrix, the algebra of matrix polynomials relative to block Toeplitz matrices can be interpreted directly in terms of the original matrix and therefore can be extended to arbitrary matrices. In fact, these polynomials turn out to provide an appropriate framework for the recently proposed generalized Levinson algorithm solving the general matrix inversion problem.     

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     

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.