This paper presents a novel algorithm for efficiently minimizing the nuclear norm of a matrix
subject to structural and semi-definite constraints. It requires performing only thresholding …

Arguably, one of the biggest challenges facing the systems and control community stems
from the exponential growth in data collection capabilities, made possible by the …

This paper considers the problem of nonparametric identification of Wiener systems in cases
where there is no a-priori available information on the dimension of the output of the linear …

Many physical phenomena, within short time windows, can be explained by low order
differential relations. In a discrete world, these relations can be described using low order …

Control oriented identification of Wiener systems is known to be a generically NP-hard
problem, even in cases where the nonlinearity is known. While convex relaxations of the …

Many practical situations involve synthesizing controllers for systems where a priori models
are not available and thus must be identified from experimental data. In most cases, it is …

Dynamic vision, a sub-area of computer vision, focuses on the problems where some sort of
gradual evolution of some variables in time (or space) exists. So the evolution of the …

This paper considers the problem of switched Wiener system identification from a Kernel
based manifold embedding perspective. Our goal is to identify both the Kernel mapping and …

It has never been easier to collect data. Ubiquitous smart phones and home appliances,
surveillance cameras in public spaces, electronic transactions, and websites browsing, are …

We consider the problem of estimating the output of an unknown discrete-time linear time-
invariant system and identifying a model of the system, where only measurements via a …