MAST 680
Topics in Applied Mathematics
Winter 2023 · Topics in Pure and Applied Mathematics
Topics
- Interpreting, analyzing, forecasting and controlling dynamic data
- Dynamic mode decomposition
- Koopman operators
- Kernel methods
- System identification
- Neural networks
- Computational scripts and notebooks for dynamical systems
Readings
- Complete instructor course notes.
- Lecture scripts and notebooks: https://github.com/jbramburger/DataDrivenDynSyst
Winter 2021 · MATH 494
Readings
- A Mathematical Introduction to Compressive Sensing by Simon Foucart and Holger Rauhut. Springer, 2013.
- Sparse and Redundant Representations by Michael Elad, Springer, 2010.
- B. Adcock and A. C. Hansen, Compressive Imaging: Structure, Sampling, Learning, Cambridge University Press (listed as forthcoming).
- Statistical Learning with Sparsity: The Lasso and Generalizations by Trevor Hastie, Robert Tibshirani, and Martin Wainwright Taylor and Francis Group, 2015.
Sources
- Course catalogue ↗2026–2027
- Syllabus or course outline ↗Winter 2023
- Historical course outline ↗Winter 2021
- Winter 2023 outline. Course header explicitly lists MATH 494, MAST 680, MAST 865. Explicitly no textbook. First-page header lists MATH 494 (MAST 680/MAST 865), whereas subsequent footers list MATH 494 (MAST 699/MAST 865); first-page header codes are preserved.
- Historical source. Generic Textbook/References headings remain requirement-unspecified. Bibliographic editions and years are retained as printed; source inconsistencies may remain. Automated extraction with conservative filtering; distinct bibliography strings screened for false positives; entire syllabus not manually reviewed.