基于向量变换的DGM(1,1,k~α)模型的病态性

系数矩阵谱条件数是度量灰色预测模型病态性的重要工具,而向量的数乘变换和旋转变换是降低系数矩阵谱条件数的有效方法.首先,利用向量的数乘变换和旋转变换研究DGM(1,1,k~α)模型的病态性,结果显示,DGM(1,1,k~α)模型的病态性主要受系数矩阵列向量的长度之比、夹角大小及时间幂的影响;其次,给出了基于向量变换的DGM(1,1,k~α)模型病态性的解决步骤;最后,通过一个算例验证了向量变换在解决矩阵病态性问题时的有效性和实用性.     

相似变换矩阵的简单求法

在研究矩阵相似问题时,如果知道矩阵A及相似变换矩阵P,则可求出与A相似的矩阵B=P~(-1)AP 反过来,如果知道A及其相似矩阵B,如何求相似变换矩阵P的问题,一般线性代数教材都很少提及它。即使个别教材中提到这个问题,也只是针对B是A的Jordan标准形的简单情形,应用解非齐次线性方程组AX=XB的方法求出相似变换矩阵P的,因B是特殊情形,所以这种方法不具有普遍意义。     

S-Nekrasov矩阵的逆矩阵无穷范数的新上界

正1引言H-矩阵逆矩阵无穷范数的估计问题在数值代数、控制论、电力系统理论等众多领域具有广泛的应用.如控制论及神经网络系统的稳定性,线性时滞系统的稳定性,以及分裂矩阵迭代法的收敛性分析等[1-5].1975年J.M.Varah针对H-矩阵的一个重要子类一严格对角占优矩阵(SDD),给出如下估计式(Varah界)[6]:     

矩阵的置换相抵和置换相似

<正> 设 A 是 m×n 矩阵,P 和 Q 分别是 m 阶和 n 阶的置换方阵,我们称 A 和 PAQ 置换相抵.当 m=n,Q=P~(-1)=P~T时(这里 M~T 表示矩阵 M 的转置矩阵),A 和 PAP~T 称为置换相似.实际上,PAQ 是分别对 A 的行作置换(通过左乘 P)和对列作置换(通过右乘Q)后所得;而 PAP~T 则是对 A 的行和列分别作同样的置换后所得.注意到在作这些置换时,A 的每个元素本身并没有改变,只是其所在的位置变动了.置换相抵和置换相似是非常特殊的矩阵相抵变换和相似变换.特别地,在不少场合,A 有相当一部分元素是0,但它们散布各处.如能在对 A 进行其它运算或处理前,先通过置换相抵或置换相似变换把A 中的0元素尽可能有规律地集中成块,从而提供一个良好的初始状态,这对解决问题来说,常有事半功倍之效.所以,可以认为,置换相抵和置换相似又是一种最基本的相抵变     

L~2(R~d)中MRA小波相位的刻画

设A是d×d实扩展矩阵,ψ是以A为扩展矩阵的小波,f是可测函数.如果对任意以A为扩展矩阵的小波ψ,fψ(其中ψ表示ψ的傅立叶变换)的逆傅立叶变换仍是以A为扩展矩阵的小波,则称f是以A为扩展矩阵的小波乘子.主要刻画了L²(R2(R^d)空间中,以行列式绝对值等于2的整数矩阵为扩展矩阵的MRA小波的线性相位.利用该结果,具体给出了二维情况下,Haar型和Shannon型小波在相似意义下的六类整数扩展矩阵的线性相位的表达形式.最后将具有线性相位的MRA不可分离小波应用到二维图象的边缘检测上.     

关于复方阵的平方根

本刊文 [1]中提出如何判断一个方阵是否存在平方根的问题 .这里 ,我们就 n阶复方阵情形给出三个判别准则 .设 A是 n阶复方阵 ,JA 表示它的若当标准形 ,则存在相似变换矩阵 P,使得 A=PJAP-1 .有关复方阵 A的若当标准形 JA 以及相似变换矩阵P的求法 ,见本刊文 [2 ]或 [3 ] ,本文不再赘述 .定义 1　设 A是 n阶复方阵 ,若存在 n阶复方阵 B,使得 B2 =A,则称 B为 A的平方根 .为书写简便 ,我们用记号 Jr( x) ( r≥ 1)与diag[B1 ,B2 ,… ,Bs]分别表示 r阶若当矩阵和对角块矩阵 :x 1 x 1x∈ Mr( C) ,B1 B2 Bs.用文 [2 ]中给出的计算复…     

四元数自共轭矩阵乘积的相似变换

本文证明了下列结果:(i)四元数矩阵A可写成两个自共轭四元数矩阵的乘积A相似于实矩阵A Hermite相似于A~*.(ii)A可写成一个半正定自共轭四元数矩阵与一个自共轭四元数矩阵的乘积A相似于实对角矩阵或者A～diag(D,I_r(×)J_2(O)),其中D是一个实对角矩阵.本文还给出了体上实矩阵AB与BA相似的一个充要条件.     

关于非负矩阵Perron特征值的上、下界

本文通过构造一可逆矩阵,对一类非负矩阵A进行若干次简单的相似变换,便可同时得到矩阵A之Perron特征值的较好的上、下界.     

一个解高度病态问题的高精度算法的数值结果

我们要解的问题是 A_x=b. (1)其中A为n×n的非奇异矩阵(可推广到亚定相容方程组),b是已知的n维向量。且矩阵A是极端病态的矩阵,即     

三阶复正交矩阵与二阶矩阵代数上的相似变换

设M_2是二阶复矩阵的全体,Φ是M_2上的线性映射.本文建立了三阶复正交矩阵与M_2上的相似变换之间的一一对应关系,并利用这一对应关系证明了Φ保Lie积行列式(谱、边缘谱)的充要条件是存在c∈{±1,±i},二阶可逆矩阵T和二阶矩阵S,使得Φ(A)=cTAT~(-1)+tr(SA)I对所有A∈M_2都成立.     

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.     

A remark on Hilbert's matrix

We exhibit a Jacobi matrix T which has simple spectrum and integer entries, and 0 commutes with Hilbert's matrix. As an application we replace the computation of the eigenvectors of Hilbert's matrix (a very ill-conditioned problem) by the computation of the eigenvectors of T (a nicely stable numerical problem).     

求解Hamilton矩阵特征值问题的一种新方法

Hamilton矩阵的特征值问题常出现在控制理论的范畴中.在最优控制系统的设计中,若状态方程为     

求解病态线性方程组的收缩Lanczos方法

Lanczos方法是求解大型线性方程组的常用方法.遗憾的是,在Lanczos过程中通常会发生算法中断或数值不稳定的情况.将给出求解大型对称线性方程组的收缩Lanczos方法,即DLanczos方法.新算法将采用增广子空间技术,在Lanczos过程中向Krylov子空间加入少量绝对值较小的特征值所对应的特征向量进行收缩.数值实验表明,新算法比Lanczos方法收敛速度更快,并且适合求解病态对称线性方程组.     

矩阵约当标准化的一个新方法

在线性和非线性问题的研究中,常需要构造一个基,使线性算子T在此基础下的矩阵表示为约当标准型,本文介绍了构造这种基的一个方法,我们从T的每个特征向量开始,通过求解一系列线性方程组而求得广义特征向量的一个链,将所有这种链放在一起,便构成想要的一组基,与通常的方法相比,这一方法较易操作,计算量小。     

On the Eigenvalues and Eigenvectors of a Lorentzian Rotation Matrix by Using Split Quaternions

In this paper, we examine eigenvalue problem of a rotation matrix in Minkowski 3 space by using split quaternions. We express the eigenvalues and the eigenvectors of a rotation matrix in term of the coefficients of the corresponding unit timelike split quaternion. We give the characterizations of eigenvalues (complex or real) of a rotation matrix in Minkowski 3 space according to only first component of the corresponding quaternion. Moreover, we find that the casual characters of rotation axis depend only on first component of the corresponding quaternion. Finally, we give the way to generate an orthogonal basis for ${\mathbb{E}^{3}_{1}}$ by using eigenvectors of a rotation matrix.     

改进的预处理共轭斜量法及其在工程有限元分析中的应用

本文就预处理共轭斜量法(PCCG法)给出了两个具有理论和实际意义的定理,它们分别讨论了迭代解的定性性质和迭代矩阵的构造原则.作者提出了新的非M-矩阵的不完全LU分解技术和迭代矩阵的构造方法.用此改进的PCCG法,对病态问题和大型三维有限元问题进行了计算并与其他方法作了对比,分析了PCCG法在求解病态方程组时的反常现象.计算结果表明本文建议的方法是求解大型有限元方程组和病态方程组的一种十分有效的方法.     

A curvilinear optimization method based upon iterative estimation of the eigensystem of the Hessian matrix

An algorithm was recently presented that minimizes a nonlinear function in several variables using a Newton-type curvilinear search path. In order to determine this curvilinear search path the eigenvalue problem of the Hessian matrix of the objective function has to be solved at each iteration of the algorithm. In this paper an iterative procedure requiring gradient information only is developed for the approximation of the eigensystem of the Hessian matrix. It is shown that for a quadratic function the approximated eigenvalues and eigenvectors tend rapidly to the actual eigenvalues and eigenvectors of its Hessian matrix. The numerical tests indicate that the resulting algorithm is very fast and stable. Moreover, the fact that some approximations to the eigenvectors of the Hessian matrix are available is used to get past saddle points and accelerate the rate of convergence on flat functions.     

Symmetric Gaussian elimination for cauchy-type matrices with application to positive definite Toeplitz matrices

The problem of solving linear equations with a Toeplitz matrix appears in many applications. Often is positive definite but ill-conditioned with many small eigenvalues. In this case fast and superfast algorithms may show a very poor behavior or even break down. In recent papers the transformation of a Toeplitz matrix into a Cauchy-type matrix is proposed. The resulting new linear equations can be solved in operations using standard pivoting strategies which leads to very stable fast methods also for ill-conditioned systems. The basic tool is the formulation of Gaussian elimination for matrices with low displacement rank. In this paper, we will transform a Hermitian Toeplitz matrix into a Cauchy-type matrix by applying the Fourier transform. We will prove some useful properties of and formulate a symmetric Gaussian elimination algorithm for positive definite . Using the symmetry and persymmetry of we can reduce the total costs of this algorithm compared with unsymmetric Gaussian elimination. For complex Hermitian , the complexity of the new algorithm is then nearly the same as for the Schur algorithm. Furthermore, it is possible to include some strategies for ill-conditioned positive definite matrices that are well-known in optimization. Numerical examples show that this new algorithm is fast and reliable. Received March 24, 1995 / Revised version received December 13, 1995     

Eigenvectors of a kurtosis matrix as interesting directions to reveal cluster structure

In this paper we study the properties of a kurtosis matrix and propose its eigenvectors as interesting directions to reveal the possible cluster structure of a data set. Under a mixture of elliptical distributions with proportional scatter matrix, it is shown that a subset of the eigenvectors of the fourth-order moment matrix corresponds to Fisher’s linear discriminant subspace. The eigenvectors of the estimated kurtosis matrix are consistent estimators of this subspace and its calculation is easy to implement and computationally efficient, which is particularly favourable when the ratio n/p is large.