整数环上一类矩阵方程Xn+Yn=λnI(n∈N,λ∈Z,λ≠0)的解

设Z,N分别是全体整数和正整数的集合,M_m(Z)表示Z上m阶方阵的集合.本文运用Fermat大定理的结果证明了:对于取定的次数n∈N,n≥3,二阶矩阵方程Xⁿ+Yⁿ=λⁿI(λ∈Z,λ≠0,X,Y∈M₂(Z),且X有一个特征值为有理数)只有平凡解;利用本原素因子的结果得到二阶矩阵方程Xⁿ+Yⁿ=(±1)ⁿI(n∈N,n≥3,X,Y∈M₂(Z))有非平凡解当且仅当n=4或gcd(n,6)=1且给出了全部非平凡解;通过构造整数矩阵的方法,证明了下面的矩阵方程有无穷多组非平凡解:■n∈N,Xⁿ+Yⁿ=λⁿI(λ∈Z,λ≠0,X,Y∈M_n(Z));X³+Y³=λ³I(λ∈Z,λ≠0,m∈N,m≥2,X,Y∈M_m(Z)).     

非单特征值引出的非线性方程分歧问题

本文讨论非线性方程f(x,λ)=θ的分歧问题,这里f:x×R→Y为非线性可微映射, x,Y为Banaclh空间.利用偏导算子A=fx(x0,λ0)的广义逆A ,研究了一类由非单特征值引出的分歧问题,给出了刻划分歧性的定理,推广了Crandall M G与Robinowitz P H的由单特征值引出的分歧性定理.     

一类奇型Sturm-Liouville算子的逆问题

研究了奇型Sturm-Liouville算子的逆问题.对于固定的n∈N,证明了Sturm-Liouville问题(1.3)-(1.5)的第n个特征值λ_n(q,H)关于H是严格单调增加的,及一组不同边界条件下的第n个特征值的谱集合{λ_n(q,H_k)}_(k=1)~(+∞)能够唯一确定(0,πr)上的势函数q(x).     

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     

具有斜特征值互逆性质的单圈图

设G是一个无向图.如果对G的任一(某个)定向图G,G的斜邻接矩阵S(G)的每一个特征值λ,其倒数1/λ同样也是S(G)的特征值,且重数与λ相同,就称G是具有强迫(允许)斜特征值互逆性质.本文确定了所有具有强迫(允许)斜特征值互逆性质的单圈图.     

带比例关系的实带状矩阵特征值反问题

研究了通过矩阵A的顺序主子矩阵A_((k))=(aij)_(i,j=1)^(n-k+1)的特征值{λ_i(n-k+1)的特征值{λ_i^((k)))}_(i=1)((k)))}_(i=1)^(n-k+1)k=1,2,…,r+1来构造一个带比例关系的实带状矩阵的特征值反问题.对当特征值{λ_i(n-k+1)k=1,2,…,r+1来构造一个带比例关系的实带状矩阵的特征值反问题.对当特征值{λ_i^((k))}_(i=1)((k))}_(i=1)^(n-k+1)中有多重特征值出现时,应当如何来构造这类矩阵进行了讨论,并给出了问题的具体算法及数值例子.     

一个从多重特征值出发的分歧定理

讨论非线性方程F(λ,u)=0的分歧问题,这里F:R×X→Y为非线性微分映射,X,Y为Banach空间,利用Lyapunov-Schmidt约化过程和隐函数定理证得一个从多重特征值出发的分歧定理.推广了Crandall M G与Rabinowitz P H的经典分歧定理.     

广义特征值问题的收缩算法

设n×n矩阵A和B组成的矩阵对(A,B)是正则的,即A+λB是一个正则束: det(A+B) 0。 考虑求解广义特征值问题 Ax=λBx, (1)由于A+λB是正则统,问题(1)恰有n个广义特征值,但当B奇异时,它包含一个     

恰含两个圈的二部图的能量

设λ1,λ2,…,λn是n阶图G的特征值,图G的能量是E(G)=|λ1| |λ2| … |λn|,设G(n)是n个顶点n 1条边的恰有两个圈的连通二部图的集合,Z(n;4,4)是G(n)中的一个图,它的两个长为4的圈恰有一个公共点,其余n-7个点都是悬挂点且均与这个公共点相邻．文中证明了Z(n;4,4)是G(n)中具有最小能量的图。     

一类二次特征值反问题的中心对称解及其最佳逼近

1引言给定n阶实矩阵M,C和K,二次特征值问题:求数λ和非零向量x使得Q(λ)x=0, (1．1)其中Q(λ)=λ2M λC K称为二次束．数λ和相应的非零向量x分别称为二次束Q(λ)的特征值和特征向量．Tisseur和Meerbergen概述了二次特征值问题的各种应用、数学理论和数值方法．在工程技术,特别是结构动力模型修正技术领域经常遇到与二次特征值问题相反的问题(称之为二次特征值反问题)．对阻尼结构进行动力分析时,应用有限元方法可得到系统的质量矩阵M,阻尼矩阵C和刚度矩阵K,从而可求得二次特征值问题的特征值(频率)和特征向量(振型)．但是有限元模型毕竟是实际结构系统的离散化,并且     

A framework for analyzing nonlinear eigenproblems and parametrized linear systems

Associated with an n×n matrix polynomial of degree , are the eigenvalue problem P(λ)x=0 and the linear system problem P(ω)x=b, where in the latter case x is to be computed for many values of the parameter ω. Both problems can be solved by conversion to an equivalent problem L(λ)z=0 or L(ω)z=c that is linear in the parameter λ or ω. This linearization process has received much attention in recent years for the eigenvalue problem, but it is less well understood for the linear system problem. We develop a framework in which more general versions of both problems can be analyzed, based on one-sided factorizations connecting a general nonlinear matrix function N(λ) to a simpler function M(λ), typically a polynomial of degree 1 or 2. Our analysis relates the solutions of the original and lower degree problems and in the linear system case indicates how to choose the right-hand side c and recover the solution x from z. For the eigenvalue problem this framework includes many special cases studied in the literature, including the vector spaces of pencils L₁(P) and L₂(P) recently introduced by Mackey, Mackey, Mehl, and Mehrmann and a class of rational problems. We use the framework to investigate the conditioning and stability of the parametrized linear system P(ω)x=b and thereby study the effect of scaling, both of the original polynomial and of the pencil L. Our results identify situations in which scaling can potentially greatly improve the conditioning and stability and our numerical results show that dramatic improvements can be achieved in practice.     

Detecting a hyperbolic quadratic eigenvalue problem by using a subspace algorithm

Numerical Algorithms - We consider the quadratic eigenvalue problem (QEP) Q(λ)x := (λ2M + λD + K)x =?0. A Hermitian QEP is hyperbolic if M is positive definite and (xHDx)2...     

p-cyclic matrices and the symmetric successive overrelaxation method

In this paper, the new functional equation, [λ?(1?ω)²]^p=λ[λ+1?ω]^p-2(2?ω)²ω^pμ^p, which connects the eigenvalues μ of a particular weakly cyclic (of index p) Jacobi matrix B to the eigenvalues λ of its associated symmetric successive overrelaxation (SSOR) matrix S_ω, is derived. This functional equation is then applied to the problem of determining bounds for the intervals of convergence and divergence of the SSOR iterative method for classes of H-matrices.     

Kirchhoff Indexes of a network

In this work we define the effective resistance between any pair of vertices with respect to a valueλ?0and a weightω on the vertex set. This allows us to consider a generalization of the Kirchhoff Index of a finite network. It turns out that λ is the lowest eigenvalue of a suitable semi-definite positive Schrödinger operator and ω is the associated eigenfunction. We obtain the relation between the effective resistance, and hence between the Kirchhoff Index, with respect to λ and ω and the eigenvalues of the associated Schrödinger operator. However, our main aim in this work is to get explicit expressions of the above parameters in terms of equilibrium measures of the network. From these expressions, we derive a full generalization of Foster’s formulae that incorporate a positive probability of remaining in each vertex in every step of a random walk. Finally, we compute the effective resistances and the generalized Kirchhoff Index with respect to a λ and ω for some families of networks with symmetries, specifically for weighted wagon-wheels and circular ladders.     

TheAB-algorithm and its properties

One presents a new algorithm, called the -algorithm, for solving the generalized eigenvalue problem Ax=λBx, where det (A—λB) ≠ 0, relative to A. The algorithm is iterative, it is based on the application of plane rotations and allows us to pass from the initial problem to the solving of a similar problem having simpler matrices, whose eigenvalues can be easily computed and coincide with the eigenvalues of the initial problem. Thus, if all the eigenvalues of the initial problem are distinct, then the application of the -algorithm leads to the computation of the eigenvalues of a pencil with triangular matrices. In the case of an arbitrary initial pencil A—λB, the problem reduces to solving the eigenvalue problem for a pencil of quasitriangular form. One proves the convergence of the algorithm. One establishes its properties which in many respects are similar with the properties of the known algorithms QR and QZ, the first of which solves the usual eigenvalue problem while the second one solves the generalized problem of the above-mentioned form.     

Isospectral flow method for nonnegative inverse eigenvalue problem with prescribed structure

The nonnegative inverse eigenvalue problem is that given a family of complex numbers λ={λ₁,…,λ_n}, find a nonnegative matrix of order n with spectrum λ. This problem is difficult and remains unsolved partially. In this paper, we focus on its generalization that the reconstructed nonnegative matrices should have some prescribed entries. It is easy to see that this new problem will come back to the common nonnegative inverse eigenvalue problem if there is no constraint of the locations of entries. A numerical isospectral flow method which is developed by hybridizing the optimization theory and steepest descent method is used to study the reconstruction. Moreover, an error estimate of the numerical iteration for ordinary differential equations on the matrix manifold is presented. After that, a numerical method for the nonnegative symmetric inverse eigenvalue problem with prescribed entries and its error estimate are considered. Finally, the approaches are verified by the numerical test results.     

一个Krasnoselski定理的推广

主要讨论了非线性方程F(λ,u)=λu-G(u)=θ的分歧问题,其中G:X→X为非线性可微映射,X为Banach空间.在G′(θ)为紧算子,N(λ~*I-G′(θ))\R(λ~*I-G′(θ))≠{θ}的条件下,利用Lyapunov-Schmidt约化过程和隐函数定理证得了方程F(λ,u)=θ在多重特征值处的分歧定理,推广了Krasnoselski的经典分歧定理.     

一类具有转向点问题的n阶近似解

用Langer变换和Olver变换求得一类具有转向点问题的n阶近似解:y(x)=v(x)ψ(x),其中ψ=λ12-14×(x2-1)14,2332=-λx∫11-τ2dτ,v(z)=A(z,λ)ξ(λ23z)+B(z,λ)'ζ(λ23z).并探讨了其特征值问题,得到λn=4n+1112,n=0,1,2….由此给出了该类问题的解的一般性结论.     

A New Implicit Iteration Process with Errors for the Family of Strongly Pseudocontractive Mappings

A method is presented for generating a sequence of lower and upper bounds for the eigenvalues of the problem (i) Tu-λSu = 0, where T and S belong to a class of unbounded and nonsymmetric operators in a separable Hilbert space. Sufficient conditions are derived for the convergence of the sequence of bounds to the eigenvalues of (i), and the applicability of the method is illustrated by approximating the smallest eigenvalue of a non-selfadjoint differential eigenvalue problem.     

Eigenvalue estimate of the basic Dirac operator on a Kähler foliation

Let F be a Kähler spin foliation of codimension q=2n on a compact Riemannian manifold M with the transversally holomorphic mean curvature form κ. It is well known [S.D. Jung, T.H. Kang, Lower bounds for the eigenvalue of the transversal Dirac operator on a Kähler foliation, J. Geom. Phys. 45 (2003) 75-90] that the eigenvalue λ of the basic Dirac operator Db satisfies the inequality , where σ∇ is the transversal scalar curvature of F. In this paper, we introduce the transversal Kählerian twistor operator and prove that the same inequality for the eigenvalue of the basic Dirac operator by using the transversal Kählerian twistor operator. We also study the limiting case. In fact, F is minimal and transversally Einsteinian of odd complex codimension n with nonnegative constant transversal scalar curvature.