Let ∆n denote the set of n×n matrices of non-negative integers which have each row and column sum equal to k. Let Λn denote the subset of all binary matrices (matrices of zeroes and ones) in ∆n. If G is a bipartite multigraph let B(G) denote the usual ‘biadjacency’ matrix of G. That is, B(G) is the matrix with rows and columns respectively corresponding to the vertices in the two parts of G, an...

For any stochastic matrix A of order n, denote its eigenvalues as λ1(A), . . . , λn(A), ordered so that 1 = |λ1(A)| ≥ |λ2(A)| ≥ . . . ≥ |λn(A)|. Let cT be a row vector of order n whose entries are nonnegative numbers that sum to n. Define S(c), to be the set of n × n row-stochastic matrices with column sum vector cT . In this paper the quantity λ(c) = max{|λ2(A)||A ∈ S(c)} is considered. The ve...

Let %I( R, S) denote the class of all m X n matrices of O’s and l’s having row sum vector R and column sum vector S. The interchange graph G( R, S) is the graph where the vertices are the matrices in %(R, S) and where two matrices are joined by an edge provided they differ by an interchange. We characterize those 81 (R, S) for which the graph C( R, S) has diameter at most 2 and those YI( R, S) ...

We present results regarding row and column spaces of matrices whose entries are elements of residuated lattices. In particular, we define the notions of a row and column space for matrices over residuated lattices, provide connections to concept lattices and other structures associated to such matrices, and show several properties of the row and column spaces, including properties that relate ...

For any stochastic matrix A of order n, denote its eigenvalues as λ1(A), . . . , λn(A), ordered so that 1 = |λ1(A)| ≥ |λ2(A)| ≥ . . . ≥ |λn(A)|. Let cT be a row vector of order n whose entries are nonnegative numbers that sum to n. Define S(c), to be the set of n × n row-stochastic matrices with column sum vector cT . In this paper the quantity λ(c) = max{|λ2(A)||A ∈ S(c)} is considered. The ve...

We provide an explicit combinatorial formula for the volume of the polytope of n× n doubly-stochastic matrices, also known as the Birkhoff polytope. We do this through the description of a generating function for all the lattice points of the closely related polytope of n × n real non-negative matrices with all row and column sums equal to an integer t. We can in fact recover similar formulas f...

Sparsified Randomization Monte Carlo (SRMC) algorithms for solving systems of linear algebraic equations introduced in our previous paper [34] are discussed here in a broader context. In particular, I present new randomized solvers for large systems of linear equations, randomized singular value (SVD) decomposition for large matrices and their use for solving inverse problems, and stochastic si...

We study the matrices Qk of in-forests of a weighted digraph Γ and their connections with the Laplacian matrix L of Γ. The (i, j) entry of Qk is the total weight of spanning converging forests (in-forests) with k arcs such that i belongs to a tree rooted at j. The forest matrices, Qk, can be calculated recursively and expressed by polynomials in the Laplacian matrix; they provide representation...

We present a construction for tight wavelet frames for nonuniform spline type spaces. Our basic requirement is that the twoscale matrices are row stochastic as this admits the local construction of a set of framelets for each scaling function. The framelets have one vanishing moment, small support, and can be designed to have symmetry properties. We apply our method to univariate splines and to...