Stochastic Processes - Einzelansicht

During the course we will discuss fundamentals and examples of stochastic processes. We will study Markov Chains and Queueing Theory.

Organisation:

Two on-site lectures every week accompanied by a tutorial/exercise where you can ask questions related to the lecture and discuss your weekly exercise assignments.

Please, register on moodle for the course, too (Link to the moodle page: https://moodle2.uni-potsdam.de/course/view.php?id=34243)

Nicolas Privault: Understanding Markov Chains, Springer 2013 (available as ebook via the UP library)

You should have basic knowledge in Probability (for example from an introductory course on stochastics) and some basics from linear algebra (matrices, eigenvalues etc).

Written or oral exam at the end of the lecture.

In the lecture Stochastic Processes, we will introduce concepts of possibly dependent sequences of random variables. These sequences can be interpreted as the time evolution of a process that is governed by randomness. 

First examples are Markov Chains, where the future of the process depends only on the present but not on the complete history of the process. This class of processes has developed great research interest in the past century and continues to be very important for applications in many subjects outside maths, too. In a second part, we will focus on Queueing Theory.

The lecture aims at students of mathematics and the applied sciences. Anyone (including students of Education) with a good understanding of basic probability theory and some linear algebra will be able to follow the course.