Functions preserving positive definiteness for sparse matrices

Positive Definiteness of Generalized Homogeneous Functions

Identification of positive definiteness of functions is crucial in control theory. However for generalized homogeneous functions, there does not exist an effective method to identify the positive definiteness. In this paper, we consider Lipschitz continuous generalized homogeneous functions. For the functions, we propose a new method to identify the positive definiteness of the functions. Moreo...

Positive definiteness of tridiagonal matrices via the numerical range

Riemannian Sparse Coding for Positive Definite Matrices

Inspired by the great success of sparse coding for vector valued data, our goal is to represent symmetric positive definite (SPD) data matrices as sparse linear combinations of atoms from a dictionary, where each atom itself is an SPD matrix. Since SPD matrices follow a non-Euclidean (in fact a Riemannian) geometry, existing sparse coding techniques for Euclidean data cannot be directly extende...

Functions Preserving Nonnegativity of Matrices

The main goal of this work is to determine which entire functions preserve nonnegativity of matrices of a fixed order n— i.e., to characterize entire functions f with the property that f(A) is entrywise nonnegative for every entrywise nonnegative matrix A of size n×n. Towards this goal, we present a complete characterization of functions preserving nonnegativity of (block) uppertriangular matri...

Differential Criteria for Positive Definiteness

We show how the Mellin transform can be used to derive differential criteria for integral representations of functions as scale mixtures, and apply this idea to derive differential criteria for positive definiteness of functions in a manner similar to that of Gneiting (1999,2001). We also give a simple derivation of Williamson’s result on multiply monotone functions (Williamson, 1956), with a l...