循环矩阵的两种特性的判定

揭示几类矩阵之间的紧密联系.借助于群的子群的判定以及循环布尔矩阵是本原矩阵的判定方法,得到循环模糊矩阵成为幂等矩阵的充要条件,反循环布尔矩阵成为本原矩阵的充要条件.并给出了循环模糊矩阵成为幂等矩阵的判定方法,反循环布尔矩阵成为本原矩阵的判定方法.     

可换对合阵组合的可逆性

先讨论两个可换对合阵P,Q线性组合aP+bQ可逆的充分必要条件及可逆时逆矩阵计算公式,再利用矩阵分解,以两种形式讨论两个可换对合阵P,Q组合aI+bP+cQ+dPQ及三个两两可换对合阵P,Q,R组合aI+bP+cQ+dPQ+eR+fPR+gQR+hPQR可逆的充分必要条件及可逆时分别给出逆矩阵计算公式.     

Completely normal matrices

Normal matrices in which all submatrices are normal are said to be completely normal. We characterize this class of matrices, determine the possible inertias of a particular completely normal matrix, and show that real matrices in this class are closed under (general) Schur complementation. We provide explicit formulas for the Moore–Penrose inverse of a completely normal matrix of size at least four. A result on irreducible principally normal matrices is derived as well.     

Williamson matrices up to order 59

A recent result of Schmidt has brought Williamson matrices back into the spotlight. In this article, a new algorithm is introduced to search for hard to find Williamson matrices. We find all nonequivalent Williamson matrices of odd order n up to n = 59. It turns out that there are none for n = 35, 47, 53, 59 and it seems that the Turyn class may be the only infinite class of these matrices.      

等差-等比循环矩阵的逆矩阵求法

本文给出了等差-等此循环矩阵的逆矩阵求法,推广文[5]的结果.     

k-广义Hermite矩阵

本文给出了k-广义(反)Hermite矩阵的概念,研究了它的性质及其与k-广义酉矩阵之间的联系,推广了酉矩阵和(反)Hermite矩阵的相应结果.     

Set inertia-preserving matrices∗ †

The inertia-preservers of several sets of matrices are identified. The sets include: all real matrices, all complex matrices, triangular matrices, real symmetric matrices and Hermitian matrices.     

Set inertia-preserving matrices

The inertia-preservers of several sets of matrices are identified. The sets include: all real matrices, all complex matrices, triangular matrices, real symmetric matrices and Hermitian matrices.     

A brief historical introduction to matrices and their applications

This paper deals with the ancient origin of matrices, and the system of linear equations. Included are algebraic properties of matrices, determinants, linear transformations, and Cramer’s Rule for solving the system of algebraic equations. Special attention is given to some special matrices, including matrices in graph theory and electrical networks. It contains a wide variety of important materials accessible to college and even high school students and teachers at all levels.     

A Family of Asymmetrical Orthogonal Arrays with Run Sizes 4p^2

Nowadays orthogonal arrays play important roles in statistics, computer science, coding theory and cryptography. The usual difference matrices are essential for the construction of many mixed orthogonal arrays. But there are also many orthogonal arrays, especially mixed-level or asymmetrical which can not be obtained by the usual difference matrices. In order to construct these asymmetrical orthogonal arrays, a class of special matrices, so-called generalized difference matrices, were discovered by Zhang（1989, 1990, 1993） by the orthogonal decompositions of projective matrices. In this article, an interesting equivalent relationship between the orthogonal arrays and the generalized difference matrices is presented. As an application, a family of orthogonal arrays of run sizes 4p2, such as L36（6^13^42^10）, are constructed.     

Taussky定理推广与应用

本文在Ｃａｓｓｉｎｉ卵形域上推广了Ｔａｕｓｓｋｙ定理。所得结果修正了Ｂｒａｕｅｒ定理,作为应用给出不可约双对角占优矩阵非奇异的充要条件,最后把基本结果推广到分块矩阵上。     

广义Nekrasov矩阵的细分迭代判别法

利用细分矩阵下标集合的思想,构造递进系数和特殊的正对角矩阵,结合不等式的放缩,给出广义Nekrasov矩阵的迭代判别法,推广和改进了已有相关结果,并用数值实例说明了所得结果的优越性.     

Elementary matrices and products of idempotents

We study the relations between product decomposition of singular matrices into products of idempotent matrices and product decomposition of invertible matrices into elementary ones.     

A new infinite family of minimally nonideal matrices

Minimally nonideal matrices are a key to understanding when the set covering problem can be solved using linear programming. The complete classification of minimally nonideal matrices is an open problem. One of the most important results on these matrices comes from a theorem of Lehman, which gives a property of the core of a minimally nonideal matrix. Cornuéjols and Novick gave a conjecture on the possible cores of minimally nonideal matrices. This paper disproves their conjecture by constructing a new infinite family of square minimally nonideal matrices. In particular, we show that there exists a minimally nonideal matrix with r ones in each row and column for any r?3.     

实正定矩阵与Minkowski不等式的再推广

本文给出实广义正定矩阵概念的新推广及其基本性质,讨论它及常见几种定义下广义正定矩阵的代数结构,得到非对称正定矩阵乘积的一个新刻画,并利用所获广义正定矩阵的性质,拓广了Minkowski,OstrowskiTaussky等矩阵不等式的取值范围.     

一类试验次数为4p2的非对称正交表的构造

Nowadays orthogonal arrays play important roles in statistics,computer science, coding theory and cryptography.The usual difference matrices are essential for the con- struction of many mixed orthogonal arrays.But there are also many orthogonal arrays, especially mixed-level or asymmetrical which can not be obtained by the usual difference matrices.In order to construct these asymmetrical orthogonal arrays,a class of special matrices,so-called generalized difference matrices,were discovered by Zhang(1989,1990, 1993) by the orthogonal decompositions of projective matrices.In this article,an interesting equivalent relationship between the orthogonal arrays and the generalized difference matri- ces is presented.As an application,a family of orthogonal arrays of run sizes 4p~2,such as L_(36)(6~13~42~(10)),are constructed.     

Effective partitioning method for computing generalized inverses and their gradients

We extend the algorithm for computing {1}, {1, 3}, {1, 4} inverses and their gradients from [11] to the set of multiple-variable rational and polynomial matrices. An improvement of this extension, appropriate to sparse polynomial matrices with relatively small number of nonzero coefficient matrices as well as in the case when the nonzero coefficient matrices are sparse, is introduced. For that purpose, we exploit two effective structures form [6], which make use of only nonzero addends in polynomial matrices, and define their partial derivatives. Symbolic computational package MATHEMATICA is used in the implementation. Several randomly generated test matrices are tested and the CPU times required by two used effective structures are compared and discussed.     

Chains of dog-ears for completely positive matrices

A necessary and sufficient condition to determine the complete positivity of a matrixwith a particular graph, in dependence of complete positivity of smaller matrices, is given. Under some singularity assumptions, this condition furnishes a characterization for completely positive matrices with a “non-crossing cycle” as associated graph. In particular the characterization holds for singular pentadiagonal matrices.     

Approximation of high-dimensional kernel matrices by multilevel circulant matrices

Kernels are important in developing a variety of numerical methods, such as approximation, interpolation, neural networks, machine learning and meshless methods for solving engineering problems. A common problem of these kernel-based methods is to calculate inverses of kernel matrices generated by a kernel function and a set of points. Due to the denseness of these matrices, finding their inverses is computationally costly. To overcome this difficulty, we introduce in this paper an approximation of the kernel matrices by appropriate multilevel circulant matrices so that the fast Fourier transform can be applied to reduce the computational cost. Convergence analysis for the proposed approximation is established based on certain decay properties of the kernels.     

On the eigenvalues of double band matrices

We consider matrices containing two diagonal bands of positive entries. We show that all eigenvalues of such matrices are of the form rζ, where r is a nonnegative real number and ζ is a pth root of unity, where p is the period of the matrix, which is computed from the distance between the bands. We also present a problem in the asymptotics of spectra in which such double band matrices are perturbed by banded matrices.