The inverse problem of bisymmetric matrices with a submatrix constraint

An n×n real matrix A is called a bisymmetric matrix if A=A^T and A=S_nAS_n, where S_n is an n×n reverse unit matrix. This paper is mainly concerned with solving the following two problems: Problem I Given n×m real matrices X and B, and an r×r real symmetric matrix A₀, find an n×n bisymmetric matrix A such that where A([1: r]) is a r×r leading principal submatrix of the matrix A. Problem II Given an n×n real matrix A^*, find an n×n matrix  in S_E such that where ∥·∥ is Frobenius norm, and S_E is the solution set of Problem I. The necessary and sufficient conditions for the existence of and the expressions for the general solutions of Problem I are given. The explicit solution, a numerical algorithm and a numerical example to Problem II are provided. Copyright © 2003 John Wiley & Sons, Ltd.     

Uniform and minimal {0,1} – cp matrices

Let A be an n?×?n real matrix. A is called {0,1}-cp if it can be factorized as A?=?BB ^T with b_ij =0 or 1. The smallest possible number of columns of B in such a factorization is called the {0,1}-rank of A. A {0,1}-cp matrix A is called minimal if for every nonzero nonnegative n?×?n diagonal matrix D, A-D is not {0,1}-cp, and r-uniform if it can be factorized as A=BB ^T, where B is a (0,?1) matrix with r 1s in each column. In this article, we first present a necessary condition for a nonsingular matrix to be {0,1}-cp. Then we characterize r-uniform {0,1}-cp matrices. We also obtain some necessary conditions and sufficient conditions for a matrix to be minimal {0,1}-cp, and present some bounds for {0,1}-ranks.     

The Constrained Solutions of Two Matrix Equations

We study the symmetric positive semidefinite solution of the matrix equation AX ₁ A ^T + BX ₂ B ^T = C, where A is a given real m×n matrix, B is a given real m×p matrix, and C is a given real m×m matric, with m, n, p positive integers; and the bisymmetric positive semidefinite solution of the matrix equation D ^T XD = C, where D is a given real n×m matrix, C is a given real m×m matrix, with m, n positive integers. By making use of the generalized singular value decomposition, we derive general analytic formulae, and present necessary and sufficient conditions for guaranteeing the existence of these solutions. Received December 17, 1999, Revised January 10, 2001, Accepted March 5, 2001     

Backward Perturbation Analysis for the Matrix Equation A~TXA+B~TYB=D

Consider the linear matrix equation A~TXA + B~TYB = D,where A,B are n X n real matrices and D symmetric positive semi-definite matrix.In this paper,the normwise backward perturbation bounds for the solution of the equation are derived by applying the Brouwer fixed-point theorem and the singular value decomposition as well as the property of Kronecker product.The results are illustrated by two simple numerical examples.     

On directional convexity

Motivated by problems from calculus of variations and partial differential equations, we investigate geometric properties of D-convexity. A function f: R ^d → R is called D-convex, where D is a set of vectors in R ^d, if its restriction to each line parallel to a nonzero v ∈ D is convex. The D-convex hull of a compact set A ⊂ R ^d, denoted by co^D(A), is the intersection of the zero sets of all nonnegative D-convex functions that are zero on A. It also equals the zero set of the D-convex envelope of the distance function of A. We give an example of an n-point set A ⊂ R ² where the D-convex envelope of the distance function is exponentially close to zero at points lying relatively far from co ^D(A), showing that the definition of the D-convex hull can be very nonrobust. For separate convexity in R ³ (where D is the orthonormal basis of R ³), we construct arbitrarily large finite sets A with co ^D(A) ≠ A whose proper subsets are all equal to their D-convex hull. This implies the existence of analogous sets for rank-one convexity and for quasiconvexity on 3 × 3 (or larger) matrices. This research was supported by Charles University Grants No. 158/99 and 159/99.     

Null ideals and spanning ranks of matrices

Let Rbe a commutative ring and A?M _m×n . The spanning rank of Ais the smallest positive integer s for which A=PQ(m×s s×n) The spanning rank of the zero matrix is set equal to zero. If Ris a field, then the spanning rank of Ais just the classical rank of A. In the first section of this paper, various theorems and examples are given which indicate how much of the classical theory of rank is still valid for spanning rank over a commutative ring. If A= PQ(n×s s×n) is a spanning rank factorization of a square matrix and D= QP, then Dis called a spanning rank partner of A. In the second part of this paper, the null ideals N _Aand N _Dof Aand Drespectively are compared. For instance, we show N _A=N _Dif s= nand N _A= XN _Dif s<nwhenever Ris a PIDand A≠0. This result sometimes (e.g. s<<n) makes the computation of N _Aeasy.     

Distance matrices for points on a line,on a circle,and at the vertices of ann-dimensional cube

Forn pointsA _i ,i=1, 2, ...,n, in Euclidean space ℝ ^m , the distance matrix is defined as a matrix of the form D=(D _i ,j) _i ,j=1,...,n, where theD _i ,j are the distances between the pointsA _i andA _j . Two configurations of pointsA _i ,i=1, 2,...,n, are considered. These are the configurations of points all lying on a circle or on a line and of points at the vertices of anm-dimensional cube. In the first case, the inverse matrix is obtained in explicit form. In the second case, it is shown that the complete set of eigenvectors is composed of the columns of the Hadamard matrix of appropriate order. Using the fact that distance matrices in Euclidean space are nondegenerate, several inequalities are derived for solving the system of linear equations whose matrix is a given distance matrix. Translated fromMatematicheskie Zametki, Vol. 58, No. 1, pp. 127–138, July, 1995.     

Reducible polar representations

In this paper the reducible polar representations of the compact connected Lie groups are classified. It turns out that there only exist “interesting” reducible polar representations of Lie groups of the types A ₃, A ₃×T ¹, B ₃, B ₃×T ¹, D ₄, D ₄×T ¹ and D ₄×A ₁. Up to equivalence, there is just one such representation of the first four Lie groups, there are three reducible polar representations of D ₄ and six of D ₄×T ¹ and D ₄×A ₁, respectively. From this follows immediately the classification of the compact connected subgroups of SO(n) which act transitively on products of spheres. Received: 28 April 2000     

Localisations of non prime e-vh-orders

Abstract

If A is an n × n complex matrix and x ∈ ? ⁿ , the conjecture is that if we take the kth power of each component of Ax, the resulting vector belongs to the range of the matrix obtained by taking the kth power of the entries of AA ^?, where A ^? is the adjoint of A. The conjecture is proved here for any k ≥ 2 when we add assumptions of either low dimension (namely, n ≤ 4) or low corank (0, 1, and, with some technical restrictions, 2). This problem arises in the study of the Jacobian Conjecture.     

Similarity to symmetric matrices over fields which are not formally real

We show that a matrix is similar to a symmetric matrix over a field of characteristic 2 if and only if the minimum polynomial of the matrix is not the product of distinct irreducible polynomials whose splitting fields are inseparable extensions. When the field is not of characteristic 2, a known theorem is generalized by considering k, the number of elementary divisors of odd degree of the n × n A: If ?1 is a sum of 2^v squares and n differs from a multiple of 2 ^{v + 1} by at most ±k, then A is similar to a symmetric matrix.     

Coloring graphs which have equibipartite complements

If G is a graph of order $2n \geq 4$ with an equibipartite complement, then G is Class 1 (i.e., the chromatic index of G is Δ (G)) if and only if G is not the union of two disjoint K_n's with n odd. Similarly if G is a graph of order 2n ≥ 6 whose complement G is equibipartite with bipartition (A, D), and if both G and B, the induced bipartite subgraph of G with bipartition (A, D), have a 1-factor, then G is Type 1 (i.e., the total chromatic number of G is Δ (G) + 1). © 1997 John Wiley & Sons, Inc. J Graph Theory 26: 183–194, 1997     

The solution of the equation AX + BX ⋆ = 0

We give a complete solution of the matrix equation AX?+?BX ^??=?0, where A, B?∈?? ^m×n are two given matrices, X?∈?? ^n×n is an unknown matrix, and ? denotes the transpose or the conjugate transpose. We provide a closed formula for the dimension of the solution space of the equation in terms of the Kronecker canonical form of the matrix pencil A?+?λB, and we also provide an expression for the solution X in terms of this canonical form, together with two invertible matrices leading A?+?λB to the canonical form by strict equivalence.     

Notes on the Kernels of Locally Finite Higher Derivations in Polynomial Rings

Let A = k^[3] be the polynomial ring in three variables over a field k, and let D be a nontrivial locally finite iterative higher derivation on A. Let A^D denote the kernel of D. In this note, we prove that, if chark > 0 and ML(A^D) ≠ A^D, then A^D ? k^[2]. As a consequence of this result, we give another proof of the cancellation theorem for k^[2] over any field k of positive characteristic.     

Generic Modules Over a Class of Drinfeld's Quantum Doubles

Let k be a field and A _n (ω) be the Taft's n ²-dimensional Hopf algebras. When n is odd, the Drinfeld quantum double D(A _n (ω)) of A _n (ω) is a Ribbon Hopf algebra. In the previous articles, we constructed an n ⁴-dimensional Hopf algebra H _n (p, q) which is isomorphic to D(A _n (ω)) if p ≠ 0 and q = ω^?1, and studied the finite dimensional representations of H _n (1, q). We showed that the basic algebra of any nonsimple block of H _n (1, q) is independent of n. In this article, we examine the infinite representations of H ₂(1, ? 1), or equivalently of H _n (1, q)?D(A _n (ω)) for any n ≥ 2. We investigate the indecomposable and algebraically compact modules over H ₂(1, ? 1), describe the structures of these modules and classify them under the elementary equivalence.     

Perturbation theory for the LDU factorization and accurate computations for diagonally dominant matrices

We present a structured perturbation theory for the LDU factorization of (row) diagonally dominant matrices and we use this theory to prove that a recent algorithm of Ye (Math Comp 77(264):2195–2230, 2008) computes the L, D and U factors of these matrices with relative errors less than 14n ³ u, where u is the unit roundoff and n × n is the size of the matrix. The relative errors for D are componentwise and for L and U are normwise with respect the “max norm” ||A||_M = max_ij |a_ij|{\|A\|_M = \max_{ij} |a_{ij}|}. These error bounds guarantee that for any diagonally dominant matrix A we can compute accurately its singular value decomposition and the solution of the linear system Ax = b for most vectors b, independently of the magnitude of the traditional condition number of A and in O(n ³) flops.     

三幂等符号模式矩阵的结构

Abstract. A matrix whose entries are , -, and 0 is called a sign pattern matrix. For a signpattern matrix A,if A3 =A, then A is said to be sign tripotent. In this paper, the characteriza-tion of the n by n(n≥2) sign pattern matrices A which are sign tripotent has been given out.Furthermore, the necessary and sufficient condition of A3=A but A2≠A is obtained, too.     

On the condition numbers associated with the polar factorization of a matrix

We are interested in the calculation of explicit formulae for the condition numbers of the two factors of the polar decomposition of a full rank real or complex m × n matrix A, where m ≥ n. We use a unified presentation that enables us to compute such condition numbers in the Frobenius norm, in cases where A is a square or a rectangular matrix subjected to real or complex perturbations. We denote by σ₁ (respectively σ _n) the largest (respectively smallest) singular value of A, and by K(A) = σ₁/σ _n the generalized condition number of A. Our main results are that the absolute condition number of the Hermitian polar factor is √2(1 + K(A)²)^1/2/(1 + K(A)) and that the absolute condition number of the unitary factor of a rectangular matrix is 1/σ _n. Copyright © 2000 John Wiley & Sons, Ltd.     

On the tournament matrices with smallest rank

A tournament matrix is a square zero-one matrix A satisfying the equation A+A^t = J ? I, where J is the all-ones matrix. In [1] it was proved that if A is an n × n tournament matrix, then the rank of A is at least (n - 1)/2, over any field; and in characteristic zero rank (A) equals n - 1 or n. Michael [3] has constructed examples having rank (n - 1)/2; they are double borderings of Hadamard tournaments of order n - 2, and so must satisfy n ≡ 1 (mod 4). In this note, we supplement this result by showing that an analogous construction is sometimes impossible when n ≡ 3 (mod 4).     

On matrices having equal corresponding principal minors

Let A, B be n × n matrices with entries in a field F. We say A and B satisfy property $\text{D}$ if B or B^t is diagonally similar to A. It is clear that if A and B satisfy property $\text{D}$, then they have equal corresponding principal minors, of all orders. The question is to what extent the converse is true. There are examples which show the converse is not always true. We modify the problem slightly and give conditions on a matrix A which guarantee that if B is any matrix which has the same principal minors as A, then A and B will satisfy property $\text{D}$. These conditions on A are formulated in terms of ranks of certain submatrices of A and the concept of irreducibility.