We consider maximum likelihood estimation of linear dynamical systems with generalized-linear observation models. Maximum likelihood is typically considered to be hard in this setting since latent states and transition parameters must be inferred jointly. Given that expectation-maximization does not scale and is prone to local minima, moment-matching approaches from the subspace identification ...

In the present paper, we develop a modified pseudospectral scheme for solving an optimal control problem which is governed by a switched dynamical system. Many real-world processes such as chemical processes, automotive systems and manufacturing processes can be modeled as such systems. For this purpose, we replace the problem with an alternative optimal control problem in which the switching t...

The Kolmogorov-Sinai entropy is a far reaching dynamical generalization of Shannon entropy of information systems. This entropy works perfectly for probability measure preserving (p.m.p.) transformations. However, it is not useful when there is no finite invariant measure. There are certain successful extensions of the notion of entropy to infinite measure spaces, or transformations with ...

Large-scale networks of dynamical systems are becoming increasingly important in science and technology. These systems arise in a variety of applications ranging from social networks, power systems, and robotics. In modeling, analysis, and control of networked systems, it is of fundamental importance to understand the interplay between network structure and underlying dynamical properties. My r...

Abstract In this chapter we define dynamical control systems over spaces previously discussed and formalize concepts as touched upon in Chap. 3 . We start by introducing continuous-time on manifolds a variety of stability notions. Then, highlight Lyapunov theory, particular, converse results. end detailing continuous few stabilization paradigms.