The course provides a foundation of mathematical principles and concepts that are needed for continued specialization within information processing and communications engineering.
- Multivariate and Complex Gaussian distributions
- Basic estimation and detection theory. Sufficient statistics, Cramér Rao bounds
- Basic information theory.
- Basic learning theory
- Matrix algebra. Complex valued vectors/matrices, Singular Value Decompositions and QR Decompositions
- Basics of optimization theory, Lagrange techniques, convexity.
- Application examples from information processing and communication systems.
