Scope and credits

• 2 lecture hours, 2 practice hours (fortnightly)
• 4.5 credits

LSF

• The Moodle contains slides, exercises and sample code

Frequency:

annually in the winter semester Please note the timetable of the module in the EWS
Course content
Data-based modelling, regression, neural networks, fuzzy systems, instance-based methods, supervised learning Optimization: gradient methods, Newton method, linear optimization, multi-criteria optimization, evolutionary optimization Applications: Identification of dynamic nonlinear systems, optimal control, optimization of complex systems, predictive control

Textbook
Nelles: Nonlinear System Identification, Springer Verlag

Examinations
Written module examination Two written assignments