非负不可约矩阵最大特征根和特征矢量的界

关于非负不可约矩阵最大特征根和特征矢量的界,已有许多作者进行了研究.例如Ledermann,Ostrowski,Brauer,Hartfiel,Schneider 等.本文目的是对上述文章中某些结果作进一步改进.     

矩阵谱半径上界的估值及非负矩阵谱半径的一个公式

<正> 本文建立了循环矩阵和非负矩阵谱半径的公式,并提出几个不等式.用这些不等式估计矩阵谱半径的上界,可得到比一般方法更精确的估计,把这些不等式作为矩阵敛散的判据,则可得到比[2]、[3]更精确、应用范围更广的结果.由于估出了谱半径的上界,故能了解矩阵特征值分布的区域.对于估计循环矩阵谱半径的上界,我们提出了一个比较精确的公式,它有时能定出循环矩阵谱半径的上确界.     

非负不可约矩阵Perron根的估计

给出了非负不可约矩阵Perron根的一些上下界估计,设A为任意非负不可约矩阵,ρ(A)为其Perron根,则ρ(A)≤max{D_k,(r_1+r_2+…r_k)/k}其中D_k为矩阵A所有k阶主子阵之列和最大值,r_1≥r_2≥…≥r_n为从大到小排序的行和,所得结果易于计算且较经典的Frobienus界值精确.同时也得到一个类似下界.     

关于既约非负矩阵优势比的界

本文改进了Ａ．Ｍ．Ｏｓｔｒｏｗｓｋｉ和佟文廷的结果,得到了关于既约非负矩阵优势比的新界．     

非负矩阵谱半径的新界值

讨论n×n阶非负矩阵的谱半径估计,给出估计其界值的新方法,该方法易于计算且能得到比"非负不可约矩阵谱半径的估计"一文中精确度更高的界,并用数值例子验证了这种方法的有效性.     

轻矩阵及其推广

在R.E.Hartwig工作的基础上进一步研究了轻矩阵,得到了轻矩阵的一些特性,且把轻矩阵推广到了广义轻矩阵,得到了广义轻矩阵的一个充要条件;部分回答了文[1]中R.E.Harwtig提出的一个公开问题：当A与B都为n除非负矩阵时,刻划方程AX=XB的非负解。     

非负矩阵最大特征值的新界值

对最大特征值的上下界进行估计是非负矩阵理论的重要部分,借助两个新的矩阵,从而得到一个判定非负矩阵最大特征值范围的界值定理,其结果比有关结论更加精确.     

非负矩阵谱半径的新界值

非负矩阵谱半径的估计是非负矩阵理论研究的重要组成部分.如果上下界能够表示为非负矩阵元素的易于计算的函数,那么这种估计价值更高.通过构造两个收敛的序列得到非负矩阵谱半径的新界值.数值算例表明其结果比有关结论更加精确.     

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     

非负矩阵谱半径的新估计

非负矩阵谱半径的估计是非负矩阵理论研究中的重要课题.如果谱半径的上下界能够表示为非负矩阵元素的易于计算的函数,那么这种估计价值更高.通过构造两个收敛的序列得到非负矩阵谱半径的新界值.数值算例表明其结果比有关结论更加精确.     

非负不可约矩阵Perron根的新下界

给出了非负不可约矩阵Perron根的一些新下界.特别的,若矩阵对角元素均相同,设为a,则(?)该结果易于计算且优于相关文献的下界.     

On polyhedra of Perron-Frobenius eigenvectors

This paper deals with the positive eigenvectors of nonnegative irreducible matrices which are merely characterized by a given upper bound u on their spectral radius and by a given matrix L of lower bounds for their elements. For any such matrix, the normalized positive left [right] eigenvector is shown to belong to the polyhedron the vertices of which are given by the normalized rows [columns] of the matrix $\text{(u}\text{I}\text{?}\text{L}\text{)}{}^{\mathrm{?1}}$. This polyhedron is proven to be also the smallest closed set which is guaranteed to contain the positive left [right] normalized eigenvector; its vertices are therefore the best componentwise bounds one can obtain on the positive eigenvectors of these matrices. A less general result has also been obtained for the symmetrical case, when the matrices are only characterized by a given lower bound l on their spectral radius and by a given matrix U of upper bounds for their elements.     

Imprimitive matrices of zeros and ones with extremal numbers of ones

In [X. Zhan, Extremal numbers of positive entries of imprimitive nonnegative matrices, Linear Algebra Appl. 424 (2007) 132–138], Zhan determined the maximum and minimum numbers of positive entries of irreducible nonnegative matrices. In this paper, we characterize the irreducible (0,1) matrices with the maximum and minimum numbers of positive entries.     

非负矩阵的一些算法

本文利用有限图论和齐次有限马尔可夫链理论的有关命题和算法得到了不同于[1]、[3]的算法:(1)有限阶非负矩阵可约性的判别、有限阶可约矩阵化为主对角线上都为不可约子块的分块三角阵的算法;(2)有限阶不可约矩阵的Frobenius表示的算法.对上述二算法本文还分别给出了直观简便的图示法.     

On Ostrowski’s disk theorem and lower bounds for the smallest eigenvalues and singular values

The paper refines the classical Ostrowski disk theorem and suggests lower bounds for the smallest-in-modulus eigenvalue and the smallest singular value of a square matrix under certain diagonal dominance conditions. A lower bound for the smallest-in-modulus eigenvalue of a product of m ≥ 2 matrices satisfying joint diagonal dominance conditions is obtained. The particular cases of the bounds suggested that correspond to the infinity norm are discussed separately and compared with some known results. Bibliography: 8 titles.     

A modified algorithm for the Perron root of a nonnegative matrix

An algorithm of diagonal transformation for the Perron root of nonnegative matrices is proposed by Duan and Zhang [F. Duan, K. Zhang, An algorithm of diagonal transformation for Perron root of nonnegative irreducible matrices, Appl. Math. Comput. 175 (2006) 762-772]. This method can be used for all nonnegative irreducible matrices. In this paper, an improved algorithm which is based on this method is proposed. The new algorithm inherits all the above-mentioned advantages of the original algorithm and has higher efficiency. It is testified by numerical testing that the efficiency of the new algorithm is improved greatly.     

Characterization of symmetric M-matrices as resistive inverses

We aim here at characterizing those nonnegative matrices whose inverse is an irreducible Stieltjes matrix. Specifically, we prove that any irreducible Stieltjes matrix is a resistive inverse. To do this we consider the network defined by the off-diagonal entries of the matrix and we identify the matrix with a positive definite Schrödinger operator whose ground state is determined by the lowest eigenvalue of the matrix and the corresponding positive eigenvector. We also analyze the case in which the operator is positive semidefinite which corresponds to the study of singular irreducible symmetric M-matrices.     

(分块)非负矩阵谱半径的界

<正>1引言若A=(a_(ij)),其中a_(ij)≥0,我们则称A为非负矩阵.ρ(A)表示A的谱半径,当A≥0时,ρ(A)就是A的Perron根.众所周知,若A≥0,则r_(min)(A)≤ρ(A)≤r_(max)(A),     

立方非负的不可约符号模式

以 ，-，0为元素的矩阵称为符号模式矩阵．本文考虑符号模式矩阵的立方模式，给出了至少含一个负元的不可约符号模式的立方模式是非负的充要条件及在置换相似下的标准型；得到了立方非负的符号模式矩阵中出现的正元素的个数的最大(小)值及给出了达到这些最大(小)值的不可约符号模式矩阵的完整刻画．