Means of positive matrices: geometry and a conjecture.
Meixner-type results for Riordan arrays and associated integer sequences.
Merging of states of Markov chains with infinite probability rates
Minimal rank.
Minimal projections onto spaces of symmetric matrices.
Minimum rank of edge subdivisions of graphs.
Moderate deviations for the spectral measure of certain random matrices
Moderate deviations for traces of words in a mult-matrix model.
Moderate deviations in a random graph and for the spectrum of Bernoulli random matrices.
Moments of characteristic polynomials enumerate two-rowed lexicographic arrays.
Monotone convergence of the Lanczos approximations to matrix functions of Hermitian matrices.
Moore-Penrose inverse of a hollow symmetric matrix and a predistance matrix
By a hollow symmetric matrix we mean a symmetric matrix with zero diagonal elements. The notion contains those of predistance matrix and Euclidean distance matrix as its special cases. By a centered symmetric matrix we mean a symmetric matrix with zero row (and hence column) sums. There is a one-toone correspondence between the classes of hollow symmetric matrices and centered symmetric matrices, and thus with any hollow symmetric matrix D we may associate a centered symmetric matrix B, and vice...
More on evaluating determinants
Multiple gcd-closed sets and determinants of matrices associated with arithmetic functions
Let f be an arithmetic function and S = {x1, …, xn} be a set of n distinct positive integers. By (f(xi, xj)) (resp. (f[xi, xj])) we denote the n × n matrix having f evaluated at the greatest common divisor (xi, xj) (resp. the least common multiple [xi, xj]) of x, and xj as its (i, j)-entry, respectively. The set S is said to be gcd closed if (xi, xj) ∈ S for 1 ≤ i, j ≤ n. In this paper, we give formulas for the determinants of the matrices (f(xi, xj)) and (f[xi, xj]) if S consists of multiple coprime...
Multiplication of free random variables and the -transform: the case of vanishing mean.
Multiplicative principal-minor inequalities for a class of oscillatory matrices.
Multiplicative semigroups of infinite dimensional matrices.
Multiscale analysis of wave propagation in random media. Application to correlation-based imaging
We consider sensor array imaging with the purpose to image reflectors embedded in a medium. Array imaging consists in two steps. In the first step waves emitted by an array of sources probe the medium to be imaged and are recorded by an array of receivers. In the second step the recorded signals are processed to form an image of the medium. Array imaging in a scattering medium is limited because coherent signals recorded at the receiver array and coming from a reflector to be imaged are weak and...
Multivariable Christoffel-Darboux kernels and characteristic polynomials of random hermitian matrices.