分块r—循环Toeplitz矩阵的特征值方程

给出了分块ｒ－循环Ｔｏｅｐｌｉｔｚ矩阵特征方程的一个求法,推广了「１」的结果。     

分块r-循环Toeplitz矩阵的特征值方程

给出了分块 r-循环 Toeplitz矩阵特征方程的一个求法 ,推广了文 [1 ]的结果 .     

一类Toeplitz线性代数方程组的预处理GMRES方法

本文研究一类来源于分数阶特征值问题的Toeplitz线性代数方程组的求解.构造Strang循环矩阵作为预处理矩阵来求解该Toeplitz线性代数方程组,分析了预处理后系数矩阵的特征值性质.提出求解该线性代数方程组的预处理广义极小残量法（PGMRES）,并给出该算法的计算量.数值算例表明了该方法的有效性.     

反厄米特型Toeplitz线性方程组的反厄米特循环预处理子

本文主要研究了带位移的反厄米特型Toeplitz线性方程组Anx=b的一个新的反厄米特循环预处理子Cn,其中矩阵An的元素是函数f（θ）=a0＋ig（θ）的傅里叶系数．如果g（θ）是Wiener类实值函数,则矩阵Cn非奇异;且当n足够大时,矩阵（Cn^-1An）·（Cn^-1An）的谱以1为聚点,数值实验进一步显示了我们的预处理子是有效的．     

分块K—循环Toeplitz矩阵求逆的快速付氏变换法

1算法描述及推导 Toeplitz矩阵及Toeplitz系统的求解在谱分析、线性预测、误差控制码、自回归滤波器设计等领域内起着重要的作用~[1-3]，而分块Toeplitz矩阵在计算机的时序分析、自回归时序模型滤波中也经常出现~[4]。对一般Toeplitz矩阵求逆，其算术复杂性为O(n~2)~[5]-[6]，其中n为Toepleitz矩阵的阶，而K-循环Toeplitz矩阵的求逆，其算术复杂性可降为O(nlog_2n)，本文提供了mn附分块K-循环Toeplitz矩阵求逆的一种快速付氏变换算法，其算术复杂性为O（mnlog_2mn）.     

对称正定Toeplitz型方程组的混合预处理

本文提出一个新的预条件子,用共轭梯度法求解对称正定的Teoplitz型线性方程组.该预处理子构造简单,易于实施快速傅里叶变换.理论和数值实验显示,我们的预处理子与T.Chan预处理子收敛性相近.     

对称Toeplitz系统的快速W变换基预条件子

１．引言考虑下列Ｎ阶线性方程组其中T_N=(t_i,j)　是Ｎ×Ｎ阶实对称正定（ＳＰＤ）Ｔｏｅｐｌｉｔｚ矩阵,即０,１,…,Ｎ－１）且Ｔ_Ｎ的所有特征值为正数．Ｔｏｅｐｌｉｔｚ系统已广泛应用于数字信号处理,时间序列分析（参见［１］）以及微分方程的数值解（参见［２１］等领域．八十年代以前,考虑到Ｔｏｅｐｌｉｔｚ矩阵的特殊性,人们主要用Ｌｅｖｉｎｓｏｎ递推技术及其变形或者分而治之思想直接求解方程组（１．１）,计算复杂性为Ｏ（Ｎ~（２））或Ｏ（ＮｌｏｇＮ~（２））（参见［３］）;比Ｇａｕｓｓ法运算量级Ｏ（Ｎ~（３）…     

无限广义块Toeplitz和Hankel矩阵求逆的统一方法

利用Sylvester位移方程的统一办法给出所谓的无限广义块Toeplitz和Hankel矩阵的求逆公式。     

基于均值的Toeplitz矩阵填充的子空间算法

本文提出一种基于均值的Toeplitz矩阵填充的子空间算法.通过在左奇异向量空间中对已知元素的最小二乘逼近,形成了新的可行矩阵;并利用对角线上的均值化使得迭代后的矩阵保持Toeplitz结构,从而减少了奇异向量空间的分解时间.理论上,证明了在一定条件下该算法收敛于一个低秩的Toeplitz矩阵.通过不同已知率的矩阵填充数值实验展示了Toeplitz矩阵填充的新算法比阈值增广Lagrange乘子算法在时间上和精度上更有效.     

无限广义块Toeplitz和Hankel矩阵求逆的统一方法

利用 Sylvester位移方程的统一办法给出所谓的无限广义块Toeplitz和 Hankel矩阵的求逆公式 .     

Preconditioned Lanczos method for generalized Toeplitz eigenvalue problems

We employ the sine transform-based preconditioner to precondition the shifted Toeplitz matrix _An−ρ_Bn$A_n-\rho B_n$ involved in the Lanczos method to compute the minimum eigenvalue of the generalized symmetric Toeplitz eigenvalue problem _Anx=λ_Bnx$A_{n}x=\lambda B_{n}x$, where _An$A_n$ and _Bn$B_n$ are given matrices of suitable sizes. The sine transform-based preconditioner can improve the spectral distribution of the shifted Toeplitz matrix and, hence, can speed up the convergence rate of the preconditioned Lanczos method. The sine transform-based preconditioner can be implemented efficiently by the fast transform algorithm. A convergence analysis shows that the preconditioned Lanczos method converges sufficiently fast, and numerical results show that this method is highly effective for a large matrix.     

Convergence of the Multigrid Method of Ill-conditioned Block Toeplitz Systems

We study the solutions of block Toeplitz systems A _mn u = b by the multigrid method (MGM). Here the block Toeplitz matrices A _mn are generated by a nonnegative function f (x,y) with zeros. Since the matrices A _mn are ill-conditioned, the convergence factor of classical iterative methods will approach 1 as the size of the matrices becomes large. These classical methods, therefore, are not applicable for solving ill-conditioned systems. The MGM is then proposed in this paper. For a class of block Toeplitz matrices, we show that the convergence factor of the two-grid method (TGM) is uniformly bounded below 1 independent of mn and the full MGM has convergence factor depending only on the number of levels. The cost per iteration for the MGM is of O(mn log mn) operations. Numerical results are given to explain the convergence rate.     

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.     

A symmetry exploiting Lanczos method for symmetric Toeplitz matrices

Several methods for computing the smallest eigenvalues of a symmetric and positive definite Toeplitz matrix T have been studied in the literature. Most of them share the disadvantage that they do not reflect symmetry properties of the corresponding eigenvector. In this note we present a Lanczos method which approximates simultaneously the odd and the even spectrum of T at the same cost as the classical Lanczos approach.     

Sine transform based preconditioners for elliptic problems

We consider applying the preconditioned conjugate gradient (PCG) method to solving linear systems Ax = b where the matrix A comes from the discretization of second-order elliptic operators with Dirichlet boundary conditions. Let (L + Σ)Σ⁻¹(L^t + Σ) denote the block Cholesky factorization of A with lower block triangular matrix L and diagonal block matrix Σ. We propose a preconditioner M = (Lˆ + Σˆ)Σˆ⁻¹(Lˆ^t + Σˆ) with block diagonal matrix Σˆ and lower block triangular matrix Lˆ. The diagonal blocks of Σˆ and the subdiagonal blocks of Lˆ are respectively the optimal sine transform approximations to the diagonal blocks of Σ and the subdiagonal blocks of L. We show that for two-dimensional domains, the construction cost of M and the cost for each iteration of the PCG algorithm are of order O(n² log n). Furthermore, for rectangular regions, we show that the condition number of the preconditioned system M⁻¹A is of order O(1). In contrast, the system preconditioned by the MILU and MINV methods are of order O(n). We will also show that M can be obtained from A by taking the optimal sine transform approximations of each sub-block of A. Thus, the construction of M is similar to that of Level-1 circulant preconditioners. Our numerical results on two-dimensional square and L-shaped domains show that our method converges faster than the MILU and MINV methods. Extension to higher-dimensional domains will also be discussed. © 1997 John Wiley & Sons, Ltd.     

Generalization of Strang's Preconditioner with Applications to Toeplitz Least Squares Problems

In this paper, we propose a method to generalize Strang's circulant preconditioner for arbitrary n-by-n matrices A_n. The th column of our circulant preconditioner Sn is equal to the th column of the given matrix A_n. Thus if A_n is a square Toeplitz matrix, then Sn is just the Strang circulant preconditioner. When Sn is not Hermitian, our circulant preconditioner can be defined as . This construction is similar to the forward-backward projection method used in constructing preconditioners for tomographic inversion problems in medical imaging. We show that if the matrix A_n has decaying coefficients away from the main diagonal, then is a good preconditioner for An. Comparisons of our preconditioner with other circulant-based preconditioners are carried out for some 1-D Toeplitz least squares problems: min ∥ b - Ax∥₂. Preliminary numerical results show that our preconditioner performs quite well, in comparison to other circulant preconditioners. Promising test results are also reported for a 2-D deconvolution problem arising in ground-based atmospheric imaging.     

Preconditioned HSS method for large multilevel block Toeplitz linear systems via the notion of matrix‐valued symbol

We perform a spectral analysis of the preconditioned Hermitian/skew‐Hermitian splitting (PHSS) method applied to multilevel block Toeplitz linear systems in which the coefficient matrix T_n(f) is associated with a Lebesgue integrable matrix‐valued function f. When the preconditioner is chosen as a Hermitian positive definite multilevel block Toeplitz matrix T_n(g), the resulting sequence of PHSS iteration matrices M_n belongs to the generalized locally Toeplitz class. In this case, we are able to compute the symbol ?(f,g) describing the asymptotic eigenvalue distribution of M_nwhen n→∞ and the matrix size diverges. By minimizing the infinity norm of the spectral radius of the symbol ?(f,g), we are also able to identify effective PHSS preconditioners T_n(g) for the matrix T_n(f). A number of numerical experiments are presented and commented, showing that the theoretical results are confirmed and that the spectral analysis leads to efficient PHSS methods. Copyright © 2015 John Wiley & Sons, Ltd.     

与正弦函数有关的星形函数逆的Toeplitz行列式

Let S*s be the class of normalized functions f defined in the open unit U = {z ∈ C:丨z丨 ＜ 1} such that the quantity zf'(z)/f(z)lies in an eight-shaped region in ...     

Circulant Preconditioners for Indefinite Toeplitz Systems

In recent papers circulant preconditioners were proposed for ill-conditioned Hermitian Toeplitz matrices generated by 2-periodic continuous functions with zeros of even order. It was show that the spectra of the preconditioned matrices are uniformly bounded except for a finite number of outliers and therefore the conjugate gradient method, when applied to solving these circulant preconditioned systems, converges very quickly. In this paper, we consider indefinite Toeplitz matrices generated by 2-periodic continuous functions with zeros of odd order. In particular, we show that the singular values of the preconditioned matrices are essentially bounded. Numerical results are presented to illustrate the fast convergence of CGNE, MINRES and QMR methods.This revised version was published online in October 2005 with corrections to the Cover Date.     

Error Analysis of the Symplectic Lanczos Method for the Symplectic Eigenvalue Problem

A rounding error analysis of the symplectic Lanczos algorithm for the symplectic eigenvalue problem is given. It is applicable when no break down occurs and shows that the restriction of preserving the symplectic structure does not destroy the characteristic feature of nonsymmetric Lanczos processes. An analog of Paige's theory on the relationship between the loss of orthogonality among the Lanczos vectors and the convergence of Ritz values in the symmetric Lanczos algorithm is discussed. As to be expected, it follows that (under certain assumptions) the computed J-orthogonal Lanczos vectors loose J-orthogonality when some Ritz values begin to converge.