特征多项式的系数

用一种新方法证明了方阵的特征多项式的一般项的系数与该方阵的主子式密切相关.利用该结论和盖尔圆盘定理,证明了0是一类特殊Laplace矩阵的单特征值.     

矩阵特征值的一类新的存在性区域

用盖尔斯果林圆盘定理估计矩阵特征值是一个经典的方法，后人对此定理虽有许多改进，例如用卵形区域代替盖氏圆盘，但都显得粗糙，本文的研究得出了一类新的特征值存在区域，它们与盖氏圆盘等方法结合结合能提高估计的精确度。     

线性离散事件动态系统的辨识

本文讨论利用输出数据来估计或确定系统矩阵特征值和特征向量问题.首先我们给出了特征值的一个估计,然后证明在一定条件下可以确定系统矩阵的特征值和特征向量,或用极限来表征它们,最后指出了所得到的结果在离散事件动态系统分析和控制中的意义.     

利用三角分解估计实对称矩阵的特征值

鉴于直接计算矩阵特征值的工作量很大,因此在实问题中,我们有时得借助于对这些特征值的某种估计。但通常基于Gerschgorin定理的估计方法往往不能对各特征值给出足够精确的界。本文则利用半正定矩阵伴随选主元的LDL~T分解提出一种估计实对称矩阵特征值的方法,所耗费的计算量是有限的,但在大多数情况下估计的精度可以得到很大的改进。本方法特别适用于半正定矩阵非零小特征值的估计,从而可用于在计算机上确定具体数值矩阵的秩。     

关于稳定矩阵分解定理的一个简单证明

一个矩阵称为稳定的,如果这个矩阵的特征值全包含在单位开圆盘内.利用Parker关于复方阵的分解定理给出了稳定矩阵分解定理的一个简单证明,并对奇异值全部严格小于1的矩阵给出了类似的结论.     

关于几类矩阵的特征值分布

<正> 在矩阵论中以及应用矩阵工具的各类问题中,估计矩阵的特征值大小与分布十分重要.在[1]中,我们给出了非负矩阵(元素全非负的矩阵)最大特征值的计算与估计方法,并将此结果推广到更广的一类矩阵.在本文中,我们将对实用中几类重要矩阵给出它们特征值分布的估计.     

带权Paneitz算子和带权圆盘振动问题的特征值不等式

本文研究光滑度量测度空间上带权Paneitz算子的闭特征值问题和带权圆盘振动问题,给出Euclid空间、单位球面、射影空间和一般Riemann流形的n维紧子流形的权重Paneitz算子和带权圆盘振动问题的前n个特征值上界估计.进一步地,本文给出带权Ricci曲率有界的紧致度量测度空间上带权圆盘振动问题的第一特征值的下界估计.     

Q-矩阵第一特征值估计的Monte Carlo方法

本文对给定的可逆马氏链所对应的 Q-矩阵给出了它的第一非零特征值的 Monte Carlo估计方法 .具体做法是通过增加一个状态构造一个新的可逆马氏链 ,然后利用增加状态的击中时分布去估计第一非零特征值 .     

关于正矩阵的最大特征值的包含定理及其应用

1　引　　言由于矩阵特征值问题在弹性动力学和自动控制等领域均已获得广泛的应用,所以关于矩阵特征值的计算方法及其上、下界的估计均为人们所关注.随着计算机的发展,有关矩阵特征值的各种有效算法应运而生[1].至于特征值的上、下界的估计问题,虽然也有很多成果[2-4],且它们在数学上都有一定的理论意义和应用价值,但常因其界限太宽而缺少工程价值.鉴于此,笔者利用文[3]引入的同步向量这一概念,讨论了正矩阵的最大特征值的上、下界的确定问题,获得了这类矩阵最大特征值的较为精确的包含定理,又与幂法[1]相结合,给出了非亏损正矩阵的最大特征…     

矩阵特征值的包含域

本文对圆盘定理进行了改进，给出了特征值分布新的估计，在此基础上得到了对角占优矩阵非奇异的一个充分条件，并且推广与改进了[1，2]中的结果。     

Numerical enclosure for multiple eigenvalues of an Hermitian matrix whose graph is a tree

In this paper we consider a numerical enclosure method for multiple eigenvalues of an Hermitian matrix whose graph is a tree. If an Hermitian matrix A whose graph is a tree has multiple eigenvalues, it has the property that matrices which are associated with some branches in the undirected graph of A have the same eigenvalues. By using this property and interlacing inequalities for Hermitian matrices, we show an enclosure method for multiple eigenvalues of an Hermitian matrix whose graph is a tree. Since we do not generally know whether a given matrix has exactly a multiple eigenvalue from approximate computations, we use the property of interlacing inequalities to enclose some eigenvalues including multiplicities.In this process, we only use the enclosure of simple eigenvalues to enclose a multiple eigenvalue by using a computer and interval arithmetic.     

求非亏损矩阵特征值的一种数值计算方法

借助相似变换将非亏损矩阵转为Hessenberg矩阵,通过获得确定Hessenberg矩阵特征多项式系数的方法,利用特征值与特征多项式系数间的关系,给出求非亏损矩阵特征值的一种数值算法。     

Mapped barycentric Chebyshev differentiation matrix method for the solution of regular Sturm-Liouville problems

In this paper, using spectral differentiation matrix and an elimination treatment of boundary conditions, Sturm-Liouville problems (SLPs) are discretized into standard matrix eigenvalue problems. The eigenvalues of the original Sturm-Liouville operator are approximated by the eigenvalues of the corresponding Chebyshev differentiation matrix (CDM). This greatly improves the efficiency of the classical Chebyshev collocation method for SLPs, where a determinant or a generalized matrix eigenvalue problem has to be computed. Furthermore, the state-of-the-art spectral method, which incorporates the barycentric rational interpolation with a conformal map, is used to solve regular SLPs. A much more accurate mapped barycentric Chebyshev differentiation matrix (MBCDM) is obtained to approximate the Sturm-Liouville operator. Compared with many other existing methods, the MBCDM method achieves higher accuracy and efficiency, i.e., it produces fewer outliers. When a large number of eigenvalues need to be computed, the MBCDM method is very competitive. Hundreds of eigenvalues up to more than ten digits accuracy can be computed in several seconds on a personal computer.     

On computation of real eigenvalues of matrices via the Adomian decomposition

The problem of matrix eigenvalues is encountered in various fields of engineering endeavor. In this paper, a new approach based on the Adomian decomposition method and the Faddeev-Leverrier’s algorithm is presented for finding real eigenvalues of any desired real matrices. The method features accuracy and simplicity. In contrast to many previous techniques which merely afford one specific eigenvalue of a matrix, the method has the potential to provide all real eigenvalues. Also, the method does not require any initial guesses in its starting point unlike most of iterative techniques. For the sake of illustration, several numerical examples are included.     

The Spectral Decomposition of Covariance Matrices for the Variance Components Models

The aim of this paper is to propose a simple method to determine the number of distinct eigenvalues and the spectral decomposition of covariance matrix for a variance components model. The method introduced in this paper is based on a partial ordering of symmetric matrix and relation matrix. A method is also given for checking straightforwardly whether these distinct eigenvalues are linear dependent as functions of variance components. Some examples and applications to illustrate the results are presented.     

Localization of eigenvalues of polynomial matrices

We consider the problem of localization of eigenvalues of polynomial matrices. We propose sufficient conditions for the spectrum of a regular matrix polynomial to belong to a broad class of domains bounded by algebraic curves. These conditions generalize the known method for the localization of the spectrum of polynomial matrices based on the solution of linear matrix inequalities. We also develop a method for the localization of eigenvalues of a parametric family of matrix polynomials in the form of a system of linear matrix inequalities.     

Domains of divergence of the USSOR method applied onp-cyclic matrices

Summary Using a recently derived classical type general functional equation, relating the eigenvalues of a weakly cyclic Jacobi iteration matrix to the eigenvalues of its associated Unsymmetric Successive Overrelaxation (USSOR) iteration matrix, we obtain bounds for the convergence of the USSOR method, when applied to systems with ap-cyclic coefficient matrix.     

A note on quaternion matrices and split quaternion matrix pencils

In this paper, localization theorems for left and right eigenvalues of a quaternion matrix are presented. Some differences between quaternion matrices and split quaternion matrices are summarized. A counter example for Gerschgorin theorems for left and right eigenvalues of a split quaternion matrix is given. Finally, a method for finding right eigenvalues of a split quaternion matrix pencil is presented.     

基于矩阵幂运算的重特征值存在性定理

对于判断矩阵重特征值的存在性问题,运用“若λ是矩阵A的特征值,则入“是Ak的特征值”这一性质,通过矩阵的迹与特征值的关系,得到了实数域上矩阵重特征值的存在性定理并给出了证明．定理实现了“由矩阵幂运算来判断矩阵重特征值的存在性”这样一个计算过程,对讨论矩阵特征值问题具有一定的启示意义．