Stochastic Processes and Filters
Data is displayed for academic year: 2023./2024.
Lecturers
Course Description
Stationary processes. Stochastic integral. Ergodic theorems. Brownian motion. White noise. Martingals. Stopping times. Stochastic diffusion. Stochastic calculus. Ito s integral. Deterministic and stochastic dynamic systems. Prediction and filtering. Wiener filter. Kalman filter. Optimal smoothers. Nonlinear filtering.
Study Programmes
Postgraduate doctoral study programme
Literature
Mohinder S. Grewal, Angus P. Andrews (2015.), Kalman Filtering, John Wiley & Sons
Athanasios Papoulis (1991.), Probability, Random Variables, and Stochastic Processes, McGraw-Hill Science, Engineering & Mathematics
Frank Beichelt (2006.), Solutions Manual for Stochastic Processes in Science, Engineering And Finance, Chapman & Hall
For students
General
ID 154760
Summer semester
6 ECTS
L0 English Level