Fast inversion algorithms for diagonal plus semiseparable matrices

Here are considered matrices represented as a sum of diagonal and semiseparable ones. These matrices belong to the class of structured matrices which arises in numerous applications. FastO(N) algorithms for their inversion were developed before under additional restrictions which are a source of instability. Our aim is to eliminate these restrictions and to develop reliable and stable numerical algorithms. In this paper we obtain such algorithms with the only requirement that the considered matrix is invertible and its determinant is not close to zero. The case of semiseparable matrices of order one was considered in detail in an earlier paper of the authors.     

Remarks on the sharp partial order and the ordering of squares of matrices

In this note we revisit the sharp partial order introduced by Mitra [S.K. Mitra, On group inverses and the sharp order, Linear Algebra Appl. 92 (1987) 17-37]. We recall some already known facts from certain matrix decompositions and derive new statements, relating our discussion to recent results in the literature concerned with partial orders between matrices and their squares.     

On polynomial EkP matrices

In this paper the relation betweenEP--matrices andE ^k P--matrices over an arbitrary filedF is studied. Further, conditions for the product ofE ^k P--matrices to be anE ^k P--matrix and for the reverse order law to hold for the polynomial Moore-Penrose inverse of the product ofE ^k P--matrices are determined     

Linear complexity algorithms for semiseparable matrices

Linear complexity algorithms are derived for the solution of a linear system of equations with the coefficient matrix represented as a sum of diagonal and semiseparable matrices. LDU-factorization algorithms for such matrices and their inverses are also given. The case in which the solution can be efficiently update is treated separately.This work was supported in part by the U.S. Army Research Office, under Contract DAAG29-83-K-0028, and the Air Force Office of Scientific Research, Air Force Systems Command under Contract AF83-0228.     

On disjoint range matrices

For a square complex matrix F and for F^∗ being its conjugate transpose, the class of matrices satisfying R(F)∩R(F^∗)={0}, where R(.) denotes range (column space) of a matrix argument, is investigated. Besides identifying a number of its properties, several functions of F, such as F+F^∗, (F:F^∗), FF^∗+F^∗F, and F-F^∗, are considered. Particular attention is paid to the Moore-Penrose inverses of those functions and projectors attributed to them. It is shown that some results scattered in the literature, whose complexity practically prevents them from being used to deal with real problems, can be replaced with much simpler expressions when the ranges of F and F^∗ are disjoint. Furthermore, as a by-product of the derived formulae, one obtains a variety of relevant facts concerning, for instance, rank and range.     

Displacement structure approach to Chebyshev-Vandermonde and related matrices

In this paper we use the displacement structure concept to introduce a new class of matrices, designated asChebyshev-Vandermonde-like matrices, generalizing ordinary Chebyshev-Vandermonde matrices, studied earlier by different authors. Among other results the displacement structure approach allows us to give a nice explanation for the form of the Gohberg-Olshevsky formulas for the inverses of ordinary Chebyshev-Vandermonde matrices. Furthermore, the fact that the displacement structure is inherited by Schur complements leads to a fastO(n ²) implementation of Gaussian elimination withpartial pivoting for Chebyshev-Vandermonde-like matrices.     

Equalities and inequalities for inertias of hermitian matrices with applications

The inertia of a Hermitian matrix is defined to be a triplet composed of the numbers of the positive, negative and zero eigenvalues of the matrix counted with multiplicities, respectively. In this paper, we show some basic formulas for inertias of 2×2 block Hermitian matrices. From these formulas, we derive various equalities and inequalities for inertias of sums, parallel sums, products of Hermitian matrices, submatrices in block Hermitian matrices, differences of outer inverses of Hermitian matrices. As applications, we derive the extremal inertias of the linear matrix expression A-BXB^∗ with respect to a variable Hermitian matrix X. In addition, we give some results on the extremal inertias of Hermitian solutions to the matrix equation AX=B, as well as the extremal inertias of a partial block Hermitian matrix.     

An algorithm for determining copositive matrices

In this paper, we present an algorithm of simple exponential growth called COPOMATRIX for determining the copositivity of a real symmetric matrix. The core of this algorithm is a decomposition theorem, which is used to deal with simplicial subdivision of on the standard simplex Δ_m, where each component of the vector β is −1, 0 or 1.     

H-矩阵和S-双对角占优矩阵

In this paper, the concept of the s-doubly diagonally dominant matrices is introduced and the properties of these matrices are discussed. With the properties of the s-doubly diagonally dominant matrices and the properties of comparison matrices, some equivalent conditions for H-matrices are presented. These conditions generalize and improve existing results about the equivalent conditions for H-matrices. Applications and examples using these new equivalent conditions are also presented, and a new inclusion region of k-multiple eigenvalues of matrices is obtained.     

Algorithms for inversion of diagonal plus semiseparable operator matrices

LetH be a Hilbert space andRHH be a bounded linear operator represented by an operator matrix which is a sum of a diagonal and of a semiseparable type of order one operator matrices. We consider three methods for solution of the operator equationRx=y. The obtained results yields new algorithms for solution of integral equations and for inversion of matrices.     

A system of real quaternion matrix equations with applications

Let H be the real quaternion algebra and H^n×m denote the set of all n×m matrices over H. Let P∈H^n×n and Q∈H^m×m be involutions, i.e., P²=I,Q²=I. A matrix A∈H^n×m is said to be (P,Q)-symmetric if A=PAQ. This paper studies the system of linear real quaternion matrix equations

     

Imbedding conditions for normal matrices

When can an (n-k)×(n-k) normal matrix B be imbedded in an n×n normal matrix A? This question was studied for the first time 50 years ago by Ky Fan and Gordon Pall, who gave the complete answer in the case k=1. Since then, a few authors obtained additional results. In this note, we show how an approach inspired by the Hermitian case can throw some light on the problem.     

Additive results for the Drazin inverse of block matrices and applications

In this paper, we consider the Drazin inverse of a sum of two matrices and derive additive formulas under conditions weaker than those used in some recent papers on the subject. As a corollary we get the main results from the paper of Yang and Liu [H. Yang, X. Liu, The Drazin inverse of the sum of two matrices and its applications, J. Comput. Appl. Math. 235 (2011) 1412-1417]. As an application we give some new representations for the Drazin inverse of a block matrix.     

Infinite triangular matrices, q-Pascal matrices, and determinantal representations

We use basic properties of infinite lower triangular matrices and the connections of Toeplitz matrices with generating-functions to obtain inversion formulas for several types of q-Pascal matrices, determinantal representations for polynomial sequences, and identities involving the q-Gaussian coefficients. We also obtain a fast inversion algorithm for general infinite lower triangular matrices.     

Multispherical Euclidean distance matrices

In this paper we introduce new necessary and sufficient conditions for an Euclidean distance matrix to be multispherical. The class of multispherical distance matrices studied in this paper contains not only most of the matrices studied by Hayden et al. (1996) 2, but also many other multispherical structures that do not satisfy the conditions in Hayden et al. (1996) 2.We also study the information provided by the origin of coordinates when it is placed at the center of the spheres and the origin representation property is satisfied. These vectors associated with the origin of coordinates generate a number of supporting hyperplanes for a family of multispherical matrices and also describe part of the null space of the corresponding distance matrices.     

Characterizations of EP matrices and weighted-EP matrices

A square complex matrix A is said to be EP if A and its conjugate transpose A^∗ have the same range. In this paper, we first collect a group of known characterizations of EP matrix, and give some new characterizations of EP matrices. Then, we define weighted-EP matrix, and present a wealth of characterizations for weighted-EP matrix through various rank formulas for matrices and their generalized inverses.     

A min-max theorem for complex symmetric matrices

We optimize the form Re x^tTx to obtain the singular values of a complex symmetric matrix T. We prove that for ,

     

Identities for minors of the Laplacian, resistance and distance matrices

It is shown that if L and D are the Laplacian and the distance matrix of a tree respectively, then any minor of the Laplacian equals the sum of the cofactors of the complementary submatrix of D, up to sign and a power of 2. An analogous, more general result is proved for the Laplacian and the resistance matrix of any graph. A similar identity is proved for graphs in which each block is a complete graph on r vertices, and for q-analogues of such matrices of a tree. Our main tool is an identity for the minors of a matrix and its inverse.