复半正定矩阵的奇异值不等式

用Mn表示所有复矩阵组成的集合.对于A∈Mn,σ(A)=(σ1(A),…,σn(A)),其中σ1(A)≥…≥σn(A)是矩阵A的奇异值.本文给出证明:对于任意实数α,A,B∈Mn为半正定矩阵,优化不等式σ(A-|α|B) wlogσ(A+αB)成立,改进和推广了文[5]的结果.     

奇异M—矩阵和广义对角占成阵的实用判定准则

1　引言和符号首先对本文所采用的符号和术语作一约定和说明,而不再重申.N表示前面n个自然数的集合,而分别用Mn(C)和Mn(R)表示所有n阶复方阵和n阶实方阵的集合,Rn表示n维实列向量.Zn={A|A=(aij)∈Mn(R),aij≤0,i≠j,i,j∈N}.若A∈Zn则称A为Z-矩阵,有时也简记为A∈Z.I恒表示适当阶的单位矩阵.设α和β为N的非空子集,对于A∈Mn(C),把由A中行标属于α而列标属于β的元素按照原来相对位置所构成的子矩阵记为A(α,β),特别地,把主子阵A(α,α)简记为A(α)、当A(α)可逆时,其逆阵记为A(α)-1,此时称矩阵A/A(α)=A(α)-A(α,α).…     

非奇异H-矩阵一类新的实用性判据

1引言在计算数学、数学物理、控制论与矩阵论中,非奇异H-矩阵是有着重要应用的一类特殊矩阵,有关其数值判定也一直是矩阵计算的重要课题,不少学者对此进行了研究,得到了许多结果,如文[1]-[10]都给出一些比较实用的判别方法．本文另提出了一些新的实用性判别,进一步改进了文[1]的主要结果．用Cn×n表示n阶复矩阵集,设A=(aij)∈Cn×n,记,若|aii|≥Λi(i=1,2,…,n)(本文用Λi表示Λi(A)),则称A为对角占优矩阵;如果每个不等号都为严格成立,则称A为严格对角占优矩阵,记A∈D;若存在正对角阵X,使得AX为严格对角占优矩阵,则称A为广义严格对角占优阵,记A∈D．设A∈Zn×n={(aij)∈Cn×n|aij≤0,i≠j;i,j∈N},若A=sI-B,s>ρ(B),其中B为非负方阵,ρ(B)表示B的谱半径,则称A为非奇异M-矩阵．若A∈Cn×n的比较矩阵M(A)=(mij)为非奇异M-矩阵,则称A为非奇异H-矩阵,其中     

局部双对角占优矩阵的注记

1引言非奇异H矩阵是计算数学、数学物理、控制论等领域中具有广泛应用的重要矩阵类,研究其充分条件自然引起人们的兴趣．文[1]中定义了一类局部双对角占优矩阵,并由此得到了非奇异H矩阵的判别方法．我们指出,文[1]所获充分条件中所给出的四个不等式条件,其中第四个不等式条件可蕴涵其余三个,进而定义了另一类局部双对角占优矩阵,并由此获得了非奇异H矩阵新的判别方法．设A=(a_(ij))∈C~(n×n),R_i(A)=sum from j≠i|a_(ij)|,i∈N={1,2,…,n}．若|a_(ii)|≥R_i(A),(?)i∈N,则称A为对角占优矩阵,记为A∈D_o;若不等式中每个不等号都是严格的,则称A为     

关于阶数为奇数的布尔矩阵行空间的基数

设Bn表示所有的n阶布尔矩阵的集合，R(A)表示A∈Bn的行空间，|R(A)|表示R(A)的基数．设m，n为正整数，本文证明了(1)Vm∈[1，46]，[1，78]，分别存在A∈B7，A∈B8，使得|R(A)|=m．(1)当n≥9为奇数时，则V m∈[1．2^(n 3)/2 2^(n 1)/2 … 2^3]．存在A∈Bm，使得|R(A)|=m．     

幂等矩阵下Yang-Baxter-like方程解的新的显式表达式

正1引言设C~(m×n)表示m×n阶复矩阵的集合,I_n表示n阶单位矩阵.对于矩阵A∈C~(m×n),A~*表示它的共轭转置矩阵.设矩阵A∈C~(n×n),如果A~2=A,则称矩阵A为幂等矩阵;如果A~2=A=A~*,则称矩阵A为正交投影矩阵.设A∈C~(n×n)本文主要研究下面的二次矩阵方程AXA=XAX,(1.1)称之为Yang-Baxter-like方程,因为其与统计物理中分别由Yang[1]和Baxter[2]独立得到的经典Yang-Baxter方程相似.     

研究简报：并行矩阵多分裂多参数松弛算法

求解大型稀疏线性方程组Ax=b，A∈L(R^n)，x，b∈R^n的并行矩阵多分裂算法最早由[1]提出，[2]提出了当系数矩阵是非奇H—矩阵时的多分裂多参数松弛算法，但是对于奇异H—矩阵的理论及算法的研究结果都很少，为此，     

有限局部环Z/q~kZ上矩阵广义逆的几个计数结果

设 R =Z/ qk Z是模整数 qk的有限局部环 ,其中 q是素数 ,k>1 .对 R上给定的 n阶矩阵 A,设 W1={X∈ Mn( R) |PAXP- 1=Q- 1XAQ, 1 P,Q∈ GLn( R) },W2 ={X∈ Mn( R) |AX =XA},W3={X∈ Mn( R) |AXA =A},W4 ={X∈ Mn( R) |XAX =X}.若 Wi≠Φ( i=1 ,2 ,3 ,4) ,用 n( Wi)表示 Wi中所有元素的个数 ,主要计算出 n( Wi) ( i =1 ,2 ,3 ,4)     

矩阵方程AXB+CYD=E对称最小范数最小二乘解的极小残差法

<正>1引言本文用R~(n×m)表示全体n×m实矩阵集合,用SR~(n×n)表示全体n×n实对称矩阵集合,OR~(n×n)表示全体n×n实正交矩阵集合.用I_n表示n阶单位矩阵,用A*B表示矩阵A与B的Hadamard乘积.对任意矩阵A,B∈R~(n×m),定义内积〈A,B〉=tr(B~T A),其中     

一类亚半正定矩阵的左右逆特征值问题(Ⅱ)

1.引言 令Rm×n表示所有m×n实矩阵集合;RN×nn表示所有非奇异的n阶实矩阵集合.令Rn×no={A∈Rn×n| X∈Rn×1:XTAX≥0},即亚半正定矩阵集合;Wr×t={A∈Rr×t|σ(A)≤1},即最大奇异值不超过1的r×t实矩阵集合,这里σ(A)表示矩阵A的最大奇异值.     

A Note on Sin Θ Theorems for Singular Subspace Variations

New perturbation theorems for bases of singular subspaces are proved. These theorems complement the known sin theorems for singular subspace perturbations, taking into account a kind of sensitivity of singular vectors discarded by previous theorems. Furthermore these results guarantee that high relative accuracy algorithms for the SVD are able to compute reliably simultaneous bases of left and right singular subspaces.     

一类奇性积分方程的多尺度配置快速算法

This paper develops fast multiscale collocation methods for a class of Fredholm integral equations of the second kind with singular kernels. A truncation strategy for the coefficient matrix of the corresponding discrete system is proposed, which forms a basis for fast algorithms. The convergence, stability and computational complexity of these algorithms are analyzed.     

Extrapolation methods for some singular fixed point sequences

A fixed point sequence is singular if the Jacobian matrix at the limit has 1 as an eigenvalue. The asymptotic behaviour of some singular fixed point sequences in one dimension are extended toN dimensions. Three algorithms extrapolating singular fixed point sequences inN dimensions are given. Using numerical examples three algorithms are tested and compared.     

A comparison between the complex symmetric based and classical computation of the singular value decomposition of normal matrices

An algorithm for computing the singular value decomposition of normal matrices using intermediate complex symmetric matrices is proposed. This algorithm, as most eigenvalue and singular value algorithms, consists of two steps. It is based on combining the unitarily equivalence of normal matrices to complex symmetric tridiagonal form with the symmetric singular value decomposition of complex symmetric matrices. Numerical experiments are included comparing several algorithms, with respect to speed and accuracy, for computing the symmetric singular value decomposition (also known as the Takagi factorization). Next we compare the novel approach with the classical Golub-Kahan method for computing the singular value decomposition of normal matrices: it is faster, consumes less memory, but on the other hand the results are significantly less accurate.     

Randomized algorithms for distributed computation of principal component analysis and singular value decomposition

Randomized algorithms provide solutions to two ubiquitous problems: (1) the distributed calculation of a principal component analysis or singular value decomposition of a highly rectangular matrix, and (2) the distributed calculation of a low-rank approximation (in the form of a singular value decomposition) to an arbitrary matrix. Carefully honed algorithms yield results that are uniformly superior to those of the stock, deterministic implementations in Spark (the popular platform for distributed computation); in particular, whereas the stock software will without warning return left singular vectors that are far from numerically orthonormal, a significantly burnished randomized implementation generates left singular vectors that are numerically orthonormal to nearly the machine precision.     

Algorithmes parallèles asynchrones pour des systèmes singuliers

In this paper we give a convergence result concerning parallel bounded delayed asynchronous algorithms for linear fixed point problems with nonexpansive linear mappings with respect to a weighted maximum norm. This allows us to propose parallel algorithms which converge to the solution of consistent singular systems, including singular M-matrices (see for more details [3]). An important characteristic of our technical framework is that we are able to describe two-stage algorithms.     

Matrices of small Toeplitz rank,certain representations of the solution to an unstable system of linear equations with Toeplitz coefficient matrices,and related fast algorithms for solving such systems

Formulas for inverting regularized systems of linear equations whose coefficient matrices are complex, Toeplitz, and singular or nearly singular are derived. They make it possible to develop economical algorithms for solving such systems in mass calculations.     

Bifurcation indicator based on meshless and asymptotic numerical methods for nonlinear poisson problems

We propose in this work new algorithms associating asymptotic numerical method and meshless discretization (MFS‐MPS: Method of fundamental solutions‐Method of particular solutions) to compute branch solutions of nonlinear Poisson problems. To detect singular points on these branches, geometrical indicator, Padé approximants, and analytical bifurcation indicator are proposed. Numerical applications show the robustness and the effectiveness of the proposed algorithms. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 30: 978–993, 2014     

解带有Hilbert核的奇异积分方程的高精度组合算法

该文给出了用求积法解带Hilber核的奇异积分方程的高精度组合算法.把网格点分成互不相交的子集合, 在子集合上并行求解离散方程组, 再利用组合算法求得全局网格点的逼近.如果积分方程的系数属于B_δ, 则求积法的精度可达O(e^-nδ). 此外, 使用组合算法不仅能得到更高的精度阶, 而且能够得到后验误差估计. 数值算例的结果表明组合算法是极其有效的.     

The Gauss-Newton method for finding singular solutions to systems of nonlinear equations

An approach to the computation of singular solutions to systems of nonlinear equations is proposed. It consists in the construction of an (overdetermined) defining system to which the Gauss-Newton method is applied. This approach leads to completely implementable local algorithms without nondeterministic elements. Under fairly weak conditions, these algorithms have locally superlinear convergence.