This course introduces the principles of model identification for non-linear dynamic systems, and provides a set of possible solution methods that are thoroughly characterized in terms of modelling assumptions and uncertainty levels. ...
In this course we will describe in numerous examples how methods from l-adic cohomology as developed by Grothendieck, Deligne and Katz can interact with methods from analytic number theory (prime numbers, modular forms etc...). ...
All fundamental principles behind modern satellite positioning to acquire, track and evaluate direct and indirect satellite signals and process them in relation to example applications: Earth monitoring (landslides,...), high precision positioning (autom ...
This class provides a hands-on introduction to data science and machine learning topics, exploring areas such as data acquisition and cleaning, regression, classification, clustering, neural networks, and visualization. The course consists of lectures and ...