n阶矩阵m次方幂的一般求法探讨

文[1]、文[2]给出了全部特征值相等及全部不同特征值为两个,并满足一定条件的n阶矩阵m次方幂的求法。本文对一般的n阶矩阵A的m次方幂A~m的求法进行探讨。本文要点: 1.提出将A~m化为次数低于n的A的多项式r(A)的一个比较简单的途径,即本文(3)式。2.对矩阵λE—A进行λ矩阵的初等变换,     

重特征值敏度的数值计算

一个结构系统的设计,往往归结为下述代数特征值问题:其中A(p)与B(p)为n×n实解析的对称矩阵,B(p)正定,λ(p)是特征值,x(p)是相应的特征向量. 设λ_1是问题(1.1)在点p=p~*的r重特征值,即存在矩阵X=(X_1,X_2)∈R~(n×n),     

一个矩阵不等式的修正及应用

设R(C)为实(复)数域,H~(n×n)为n×n的Hermitian矩阵的集合。当A(∈C~(n×n))的特征值皆为实数时,如不特殊说明,约定A的特征值满足λ_1(A)≥…≥λ_n(A)。文[1]有如下不等式, 令A=B=[(?)],知(1)式一般不成立,(1)式是[1]将[2]的关于奇异值不等式     

合同下矩阵特征值与T合同下矩阵奇异值的估计

本文讨论了 *合同下 Hermite矩阵的诸特征值及 T合同下对称矩阵 (实或复 )的诸奇异值的变化情况 ,给出的结果改进了 Sylvester,Ostrowski[1] 等人的相应结果 .另外 ,本文还得到了两 Hermite矩阵乘积的特征值和两复矩阵乘积的奇异值的估计 ,改进并推广了 Sha Huyn[3 ] 、郁易生[4 ] 、周金士[5] 等人的结果     

p.n.p.矩阵的一些性质

一个n阶实方阵若其各阶主子式皆非正,则称为部分非正阵,简写作p.n.p.矩阵.特别地,各阶主子式皆负的p.n.p.矩阵称为部分负矩阵,简写为p.n.矩阵。文[1]、[5]讨论了p.n.p.矩阵的谱性质。本文在[5]的基础上讨论了p.n.p.矩阵的若干性质,并给出p.n.p.矩阵特征值的某些估计式。 引理1 设A=(A_(ij)_n×n为一p.n.p.矩阵,则A的特征值之实部不全为负(n≥2)。 证 设λ_1,λ_2,…,λ_n为A的全部特征值。假定A的每一特征值之实部皆为负。分两种情     

共轭广义对角占优矩阵的特征值分布

文献[1]和[2]分别给出了复方阵A在准严格对角占优和共轭准严格对角占优(由定义知它包含了严格对角占优类和共轭严格占优类)条件下的特征值分布。[6]对此作了进一步的研究。这些结果对矩阵特征值理论和特殊矩阵理论有着重要的意义。 本文导出了复方阵A在广义对角占优和共轭广义对角占优条件下的特征值分布。由于广     

四元数自共轭矩阵乘积的特征值不等式

由于四元数对乘法无交换律,因而对四元数自共轭矩阵的特征值问题的讨论比复数矩阵的相应问题要困难得多,文[1]、[2]分别对四元数自共轭矩阵的特征值和两个四元数自共轭矩阵乘积的特征进行了估计,做了一定的工作,但与复数域上的有关结果相比较,还有较大差距.本文对四元数自共轭矩阵乘积的特征值进行了探讨.得到了较好的结论,推广了[1]、[2]中的结果。     

具有四个不同特征值的竞赛矩阵

设A是n阶竞赛矩阵，k是非负整数。文[3]刻划了恰好有三个不同特征值的n阶竞赛矩阵，文[4]刻划了恰好有四个不同特征值并且0作为一个一重特征值的n阶竞赛矩阵。在这篇文章中我们主要研究了两个问题：（1）讨论当k是A的特征值时A的性质。（2）刻划恰好有四个不同特征值并且k作为一个一重特征值的全部n阶竞赛矩阵。     

一类Hermitian鞍点矩阵的特征值估计

本文研究了一类大型稀疏Hermitian鞍点线性系统Az=(B E E* 0)(x y)=(f g)=b系数矩阵的特征值,其中B∈C~(p×p)是Hermitian正定阵矩阵,E∈C~(p×q)是列降秩.本文分别给出了该系数矩阵正特征值与负特征值界的一个估计式,同时通过数值算例验证本文所给出的特征值界的估计是合理且有效的.     

由特征值唯一确定的实3×3Hankel矩阵(英文)

本文研究了由特征值唯一确定的3×3实Hankel矩阵.借助于M.Fielder[1]的结论并经过细致的讨论,得到3×3实Hankel矩阵由其特征值唯一确定的充分必要条件,刻画了3×3实Hankel矩阵的一种特征值性质.     

Perturbation behavior of a multiple eigenvalue in generalized Hermitian eigenvalue problems

We show that a multiple eigenvalue has different sensitivities under perturbations in a generalized Hermitian eigenvalue problem. Our result provides a solution to a question raised by Stewart and Sun. We also show how this difference of sensitivities plays a role in the eigenvalue forward error analysis after the Rayleigh-Ritz process, for which we present an approach that provides tight bounds.     

Finite-dimensional optimality conditions: B-gradients

The B-gradients are a convex set of generalized gradients contained in Clarke's generalized gradients. These gradients retain many of the nice properties of Clarke's generalized gradients. In this paper, necessary conditions for optimality in finite-dimensional perturbed optimization problems are given. A calmness condition is used for a constraint qualification.     

Generalized sensitivity analysis in a delay system

It is shown that abstract formulations of state dependent delay equations are useful for numerical computations of sensitivities and generalized sensitivities for such equations. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

On generalized gradients

In this paper we present a concept of the construction of generalized gradients by considering a development of directional derivatives into spherical harmonics. This leads to a derivation system as a system of generalized partial derivatives. Necessary conditions for local extrema for a broad class of not necessarily differentiable function can be given and a characterization of points of differentiability can be proved by using generalized gradients.     

Optimality conditions for non-lipschitz generalized convex programming via clarke-rockafellar gradients

For nonlinear programs with non-Lipschitz. generalized con\ex data functions. we develop various explicit first-order sufficient and /or necessary optimality conditions. These involve a natural generalization of the well known Karush-Kuhn-Tucker conditions, but with the familiar gradient condition modified so as to involve asymptotic (i.e. singular), as well as ordinary, Clarke-Rockafellar generalized gradients. In this way we cover situations in which the sets of ordinary generalized gradients are empty or unbounded, which can occur even at points where the functions are finite everywhere nearby. Along wit the use of asymptotic gradients, the novelty here lies in the identification of weak hypotheses on the data functions suitable for deriving such optimality results. In particular. the notions of protoconvexity is found to play a central role. along with the more familiar notions of quasiconvexity and’ pseudoconvexity     

Generalized estimates for performance sensitivities of stochastic systems

Three kinds of estimates for performance sensitivities (gradients, Hessians etc.) of stochastic systems are introduced. These estimates are given in general operator form. Their convergence conditions and rate of convergence are presented. Particular attention is given to estimates obtained from a single sample path. Various examples of estimates are considered.     

Optimality and duality in vector optimization involving generalized type I functions over cones

In this paper generalized type-I, generalized quasi type-I, generalized pseudo type-I and other related functions over cones are defined for a vector minimization problem. Sufficient optimality conditions are studied for this problem using Clarke’s generalized gradients. A Mond-Weir type dual is formulated and weak and strong duality results are established.     

A representation-theoretical proof of Bransonʼs classification of elliptic generalized gradients

The purpose of this paper is to present a new proof of Branson?s classification (Branson, 1997 [3]), of minimal elliptic sums of generalized gradients. The advantage of this proof is that it is local, being mainly based on representation theory and on the relationship between ellipticity and refined Kato inequalities. This approach is promising for the classification of elliptic generalized gradients of G-structures, for other subgroups G of the special orthogonal group.     

Generalized method of conjugate gradients for the solution of linear systems

We obtain convergence criteria for the generalized method of conjugate gradients for solving systems of linear algebraic equations; they imply the convergence of the method in a finite number of steps. The theorem proved in the paper allows at the same time to consider the known variants of the generalized method of conjugate gradients, as well as to devise new modifications for the convergence of this method.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 80, pp. 181–188, 1978.     

The Structure of Clarke's Generalized Gradient andComputing Some of Its Element for the SmoothComposition of Max-Type Functions

1.IntroductionConsidersmoothcompositionsofmax-typefunctionsoftheform:f(x)=g(x,aestfij(x),'',,T?:fmj(x)),(1.1)wherexER",Ji,i~1,'',marefiniteindexsets,gandfij,jEJi,i=1,'',marecontinuouslydifferentiableonRill 71andR;'respectively.Thisclassofnonsmoothfunct…