Advanced measurement techniques and high-performance computing have made large
data sets available for a range of turbulent flows in engineering applications. Drawing on …

This book presents an overview of the different errors-in-variables (EIV) methods that can be
used for system identification. Readers will explore the properties of an EIV problem. Such …

Several problems in modeling and control of stochastically driven dynamical systems can be
cast as regularized semidefinite programs. We examine two such representative problems …

In this paper, we extend the Beta divergence family to multivariate power spectral densities.
Similarly to the scalar case, we show that it smoothly connects the multivariate Kullback …

In this technical note, we deal with a spectrum approximation problem arising in THREE-like
multivariate spectral estimation approaches. The solution to the problem minimizes a …

In this letter we propose an identification procedure of a sparse graphical model associated
to a Gaussian stationary stochastic process. The identification paradigm exploits the …

We approximate a given rational spectral density by one that is consistent with prescribed
second-order statistics. Such an approximation is obtained by selecting the spectral density …

Spectral estimation can be performed using the so called THREE-like approach. Such
method leads to a convex optimization problem whose solution is characterized through its …

Motivated by graphical models, we consider the “Sparse Plus Low-rank” decomposition of a
positive definite concentration matrix-the inverse of the covariance matrix. This is a classical …

A parametric spectral estimation problem in the style of Byrnes, Georgiou, and Lindquist was
posed in [1], but the existence of a solution was only proved in a special case. Based on …