-matrices, discrepancy and preservers
Let and be positive integers, and let and be nonnegative integral vectors. Let be the set of all -matrices with row sum vector and column vector...
Let and be positive integers, and let and be nonnegative integral vectors. Let be the set of all -matrices with row sum vector and column vector...
For integers , Brietzke (2008) defined the -central coefficients of an infinite lower triangular matrix as , with , and the -central coefficient triangle of as It is known that the -central coefficient triangles of any Riordan array are also Riordan arrays. In this paper, for a Riordan array with and , we obtain the generating function of its -central coefficients and give an explicit representation for the -central Riordan array in terms of the Riordan array . Meanwhile, the...
An sign pattern is said to be potentially nilpotent if there exists a nilpotent real matrix with the same sign pattern as . Let be an sign pattern with such that the superdiagonal and the entries are positive, the
A sign pattern is a sign pattern if has no zero entries. allows orthogonality if there exists a real orthogonal matrix whose sign pattern equals . Some sufficient conditions are given for a sign pattern matrix to allow orthogonality, and a complete characterization is given for sign patterns with to allow orthogonality.
We consider inhomogeneous matrix products over max-plus algebra, where the matrices in the product satisfy certain assumptions under which the matrix products of sufficient length are rank-one, as it was shown in [6] (Shue, Anderson, Dey 1998). We establish a bound on the transient after which any product of matrices whose length exceeds that bound becomes rank-one.
We analyze a boundary-value problem for linear partial differential algebraic equations, or PDAEs, by using the method of the separation of variables. The analysis is based on the Kronecker-Weierstrass form of the matrix pencil[A,-λ_n B]. A new theorem is proved and two illustrative examples are given.
Given a square matrix A, a Brauer’s theorem [Brauer A., Limits for the characteristic roots of a matrix. IV. Applications to stochastic matrices, Duke Math. J., 1952, 19(1), 75–91] shows how to modify one single eigenvalue of A via a rank-one perturbation without changing any of the remaining eigenvalues. Older and newer results can be considered in the framework of the above theorem. In this paper, we present its application to stabilization of control systems, including the case when the system...