Modelreduction - Interactive curriculae of TU Ilmenau

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module properties Modelreduction in degree program Master Data Science 2026
module number	201321
examination number	2400928
department	Department of Mathematics and Natural Sciences
ID of group	2416 (Analysis and Dynamical Systems)
module leader	Prof. Dr. Timo Reis
term	winter term only
language	Englisch
credit points	5
on-campus program (h)	34
self-study (h)	116
obligation	elective module
exam	oral examination performance, 30 minutes
details of the certificate
link to Moodle course
teacher
signup details for alternative examinations
maximum number of participants
previous knowledge and experience
learning outcome	After the course, the students are familiar with the fundamental techniques of model reduction. They have the ability to apply general results to specific cases. They are able to analyze concrete application examples. They also understand how model reduction methods can be computationally implemented.
content	Model reduction methods in mathematical systems theory, particularly balanced truncation, frequency-domain interpolation methods, Krylov subspace methods, and principal component method. Numerical methods for solving high-dimensional Lyapunov and Riccati equations, especially Smith, ADI, and Newton-Kleinman methods.
media of instruction and technical requirements for education and examination in case of online participation	Blackboard, beamer, script (blackboard, projector, script)
literature / references	- Antoulas, Athanasios C. (2005). Approximation of Large-Scale Dynamical Systems. SIAM. - Benner, Peter; Fassbender, Heike (2014), "Model Order Reduction: Techniques and Tools" (PDF), Encyclopedia of Systems and Contro - Antoulas, A. C.; Sorensen, D. C.; Gugercin, S. (2001), "A survey of model reduction methods for large-scale systems" (PDF), Structured matrices in mathematics, computer science, and engineering, I (Boulder, CO, 1999), Contemporary Mathematics, vol. 280, Providence, RI: American Mathematical Society, pp. 193-219, - Benner, Peter; Cohen, Albert; Ohlberger, Mario; Willcox, Karen (2017). Model Reduction and Approximation: Theory and Algorithms. SIAM Publications
evaluation of teaching