正规矩阵的任意扰动

设A为n×n矩阵,其特征值为λ1,λ2,…,λn;矩阵B=A+X之特征值为μ1,μ2,…,μn.若A,B均为正规矩阵,由Wielandt-Hoffman定理[1],存在1,2,…,n的一个排列k1,k2,…,kn,使得nj=1|λj-μkj|2≤‖X‖2F,(1)其中‖·‖F表示Frobenius范数.又,在同样条件下,存在1,2,…,n的一个排列l1,l2,…,ln,使得对1≤j≤n均有|λj-μlj|≤2.91‖X‖2,(2)其中‖·‖2表示谱范数,这是R.Bhatia等人的结果[2].本文旨在讨论A为正规矩阵,B为任意矩阵时特征值的扰动估计,得到了几个扰动定理,分别推广了上述两个结果.本文用CH表示矩阵C的共轭转置,trC表示C的迹;…     

一类矩阵对的广义特征值的扰动界限

关于矩阵特征值的扰动,下面的结果是熟知的:若A与C皆为n阶正规矩阵,它们的特征值分别为α_1,…,α_n与γ_1,…,γ_n,则据Wielandt-Hoffman定理,存在1,…,n的一个排列k_1,…,k_n,使得     

关于矩阵范数的几个不等式

正1引言文中,用M_n表示n×n复矩阵全体,用‖·‖表示任意的酉不变范数,分别用|λ_n(A)|≤…≤|λ_1(A)|,s_n(A)≤…≤s1(A)来表示矩阵A的特征值和奇异值,用|A|=(A~*A)~(1/2)表示A的绝对值算子.     

任意矩阵的特征值的扰动估计

设A和B是两个任意的n阶方阵,其特征值分别为{λ_1,…,λ_n}和{μ_1,…,μ_n}.本文对此两组特征值的如下“距离”的界给出了若干估计: B对于A的谱改变量 A与B的特征值的改变量这里的结果包含了Bauer-Fike定理,并且优于Kahan-Parlett/Jiang定理及Chu,施和肖所得出的结果.     

关于Kahan定理的一个注记

设A∈C~(n×n),B∈C~(k×k)均为Hermite矩阵,它们的特征值分别为{λ_j}_(j=1)~n和{μ_j}_(j=1)~k(k≤n);Q∈~(n×k)为列满秩矩阵.令 (1) 则存在A的k个特征值λ_(j_2),λ_(j_2),…,λ_(j_k),使得 (2) 其中σ_k为Q的最小奇异值,||·||_2表示矩阵的谱范数.这是著名的Kahan定理·1996年曹志浩等在[2]中将(2)加强为 (3) 这是Kahan的猜想.在本文中,我们讨论将Kahan定理中“B为k阶Hermite矩阵”改为B为k阶(任意)方阵后,特征值的扰动估计,有以下结果. 定理 设A∈C~(n×n)为Hermite矩阵,其特征值为{λ_j}_(j=1)~n,B∈C~(k×k)的特征值为{μ_j}_(j=1)~k,而Q∈C~(n×k)为列满秩矩阵.则存在A的k个特征值λ_(j_1),λ_(j_2),…,λ_(j_k),使得     

矩阵反问题解的稳定性

首先说明一些记号.C~(m×n):所有m×n复元素矩阵的全体,C_r~(m×n):C~(m×n)中所有秩为r的矩阵的全体.A~H:矩阵A的转置共轭.I~((n)):n行列单位矩阵.A>0表示A是正定Hermite矩阵,λ_(max)(A)与λ_(min)(A)分别表示Hermite矩阵A的最大与最小特征值,σ_(max)(A)与σ_(min)(A)分别表示矩阵A的最大与最小奇异值.A~+:A的Moors-Penrose广义逆.|| ||_2:矩阵的谱范数,|| ||_F:矩阵的Frobenius范数.     

关于正规矩阵特征值的扰动

设N与A均为n×n正规矩阵,其特征值分别为{v_i}_(i=1)~n与{α_i}_(i=1)~n。Hoffman和Wielandt证明了:存在1,2,…,n的一个排列π(1),π(2),…,π(n),使得|| ||_F表示Frobenius范数。 当N为n×n Hermite矩阵,A为n×n可对称化矩阵,即存在非奇异矩阵Q=I X,使得Q~(-1)AQ为Hermite矩阵时,Stewart证明了:如果N与A的特征值分别     

规范矩阵乘积的特征值的最优估计

文[1]给出了下面的定理: 设A,B为两个n×n(n>1)阶正定厄米特矩阵;μ_1,…μ_4;ν_1,…ν_n分别为A,B的特征值,     

非齐次对称特征值问题

引言 用SR~(n×n)表示所有。n×n实对称矩阵的集合。R~n表示n维线性空间。||·||_2表示向量的Euclid范数或矩阵的谱范数。 本文研究如下问题: 问题ISEP 给定矩阵A∈SR~n×n和向量b∈R~n,求实数λ和向量X∈R~n使得 AX=λX+b, (1) ||X||_2=1. (2) 若b=0,则问题ISEP就是通常的实对称矩阵特征值问题,若b≠0,则问题ISEP称为非齐次对称特征值问题,使(1)和(2)式成立的数λ和向量X分别称为非齐次特征值和相应的非齐     

关于两个正定矩阵之积的特征值估计的一个注记

令A>0及B>0记两个n×n(n≥2)厄尔米特正定矩阵;μ_1≥μ_2≥…μ_n及ν_1≥ν_2≥…≥ν_n记A和B的特征值;设λ为AB的任意特征值.ShaHu-yun证得2/nμ_n~2ν_n~2/μ_n~2 ν_n~2<λ相似文献   

A distance bound for pseudospectra of matrix polynomials

In this note, we obtain a lower bound for the distance between the pseudospectrum of a matrix polynomial and a given point that lies out of it, generalizing a known result on pseudospectra of matrices.     

循环图的距离能量（英文）

For a connected graph G, the distance energy of G is a recently developed energytype invariant, defined as the sum of absolute values of the eigenvalues of the distance matrix G. A graph is called circulant if it is Cayley graph on the circulant group, i.e., its adjacency matrix is circulant. In this note, we establish lower bounds for the distance energy of circulant graphs. In particular, we discuss upper bound of distance energy for the 4-circulant graph.     

On the second smallest distance between finitely many points on the sphere

In the following note we investigate the second smallest distance between finitely many points on the sphere. Actually we look for the smallest upper bound for the second smallest distance between n points on the unit sphere. We solve this problem for n=9 and also we give a general, non-trivial upper bound for the second smallest distance of n points with n9.Supported by the Hungarian National Foundation for Scientific Research, Number 1238.     

On condition numbers of polynomial eigenvalue problems

In this paper, we investigate condition numbers of eigenvalue problems of matrix polynomials with nonsingular leading coefficients, generalizing classical results of matrix perturbation theory. We provide a relation between the condition numbers of eigenvalues and the pseudospectral growth rate. We obtain that if a simple eigenvalue of a matrix polynomial is ill-conditioned in some respects, then it is close to be multiple, and we construct an upper bound for this distance (measured in the euclidean norm). We also derive a new expression for the condition number of a simple eigenvalue, which does not involve eigenvectors. Moreover, an Elsner-like perturbation bound for matrix polynomials is presented.     

Maximal and minimal entry in the principal eigenvector for the distance matrix of a graph

Let G=(V,E) be a simple, connected and undirected graph with vertex set V(G) and edge set E(G). Also let D(G) be the distance matrix of a graph G (Jane?i? et al., 2007) [13]. Here we obtain Nordhaus–Gaddum-type result for the spectral radius of distance matrix of a graph.A sharp upper bound on the maximal entry in the principal eigenvector of an adjacency matrix and signless Laplacian matrix of a simple, connected and undirected graph are investigated in Das (2009) [4] and Papendieck and Recht (2000) [15]. Generally, an upper bound on the maximal entry in the principal eigenvector of a symmetric nonnegative matrix with zero diagonal entries and without zero diagonal entries are investigated in Zhao and Hong (2002) [21] and Das (2009) [4], respectively. In this paper, we obtain an upper bound on minimal entry in the principal eigenvector for the distance matrix of a graph and characterize extremal graphs. Moreover, we present the lower and upper bounds on maximal entry in the principal eigenvector for the distance matrix of a graph and characterize extremal graphs.     

Estimation of the Separation of Two Matrices (Ⅱ)

In this paper we give a lower bound of the separation $sep_F(A,B)$ of two diagonalizable matrices A and B. The key to finding the lower bound of $sep_F(A,B)$ is to find an upper bound for the condition number of a transformation matrix Q which transforms a diagonalizable matrix A to a diagonal form. The obtained lower bound of $sep_F(A,B)$ involves the eigenvalues of A and B as well as the departures form the normality $\delta_F(A)$ and $\delta_F(B)$.     

矩阵F分布渐近正态分布的一种方式(英文)

本文主要讨论矩阵F分布的一致渐近正态性.通过计算矩阵F分布和多元正态分布的Kullback-Leibler距离,找到了矩阵F分布一致渐近正态分布的条件.     

Subgroup normality degrees of finite groups I

In this paper, we introduce the probability that a subgroup H of a finite group G can be normal in G, the subgroup normality degree of H in G, as the ratio of the number of all pairs \({(h, g)\in H\times G}\) such that \({h^g\in H}\) by |H||G|. We give some upper and lower bounds for this probability and obtain the upper bound \({\frac{8}{15}}\) for nontrivial subgroups of finite simple groups. In addition, we obtain explicit formulas for subgroup normality degrees of some particular classes of finite groups.     

On the stability of large matrices

The distance rstab(A) of a stable matrix A to the set of unstable matrices and the norm of the exponential of matrices constitute two important topics in stability theory. We treat in this note the case of large matrices. The method proposed partitions the matrix into two blocks: a small block in which the stability is studied and a large block whose field of values is located in the complex plane. Using the information on the blocks and some results on perturbation theory, we give sufficient conditions for the stability of the original matrix, a lower bound of rstab(A) and an upper bound on the norm of the exponential of A. We illustrate these theoretical bounds on a practical test problem.     

A Note on Burkholder Integrals

In this note, for $k$-quasiconformal mappings of a bounded domain into the complex plane, we give an upper bound of Burkholder integral. Moreover, as an application we obtain an upper bound of the $L^p$-integral of $\sqrt{J_f}$ and $|Df|$ for certain $K$-quasiconformal mappings.