There are nine lectures in the course:
Lecture1: Introduction, the model-order-reduction problem. Examples.
Lecture 2: Model truncation, singular perturbation.
Lecture 3: Linear systems: POD/PCA/SVD-based simplifiction.
Lecture 4: Linear systems: Gramians and balanced realizations.
Lecture 5: Balanced truncation and weighted extensions.
Lecture 6: Applications; controller and nonlinear model reduction.
Lecture 7: Optimal model reduction: Hankel norm approximation .
Lecture 8:System identification and model reduction in H2-norm (guestlecture).
Lecture 9: Summary