Course 6.242 (Fall 2004) - Syllabus

• Objectives and challenges of model reduction (1) [ps.gz] [pdf]
• Order and complexity of system models (1) [ps.gz] [pdf]
• Quality of system approximation (1.5) [ps.gz] [pdf]
• Projection-based model reduction (1.5) [ps.gz] [pdf]
• LTI balanced truncation (3, draft) [ps.gz] [pdf]
• Proper orthogonal decomposition (1) [ps.gz] [pdf]
• Model reduction via moments matching (2) [ps.gz] [pdf]
• LTI system approximation via orthonormal decomposition (2) [ps.gz] [pdf]
• LTI model reduction via convex optimization (4) [ps.gz] [pdf]
• Hankel optimal LTI model reduction (4) [ps.gz] [pdf]
• Model reduction of uncertain models (2.5) [ps.gz] [pdf]
• Model reduction of parameter-dependent models (draft) [ps.gz] [pdf]
• Structure-preserving model reduction
• Model reduction for hidden Markov models
• Complexity and accuracy of matrix computations
• Model reduction and system identification