— We define the concept of approximate domain optimizer for deterministic and expected value optimization criteria. Roughly speaking, a candidate optimizer is an approximate dom...
Andrea Lecchini-Visintini, John Lygeros, Jan M. Ma...
This paper considers consensus problems with delayed noisy measurements, and stochastic approximation is used to achieve mean square consensus. For stochastic approximation based c...
— For the optimal approximation of multivariate Gaussian densities by means of Dirac mixtures, i.e., by means of a sum of weighted Dirac distributions on a continuous domain, a n...
In this paper we consider the problem of inducing a transition in a controlled quantum mechanical system whose spectrum loses simplicity for some values of the control. We study th...
Ugo V. Boscain, Francesca C. Chittaro, Paolo Mason...
In this paper, we investigate limiting behavior of linear dynamic systems driven by random stochastic matrices. We introduce and study the new concepts of partial ergodicity and 1-...