In the first part of the course the following topics are covered:
- A rigorous revisit of basic principles in digital communication,
- Stochastic processes and stationary discrete‐time stochastic processes,
- Binary and multi‐hypothesis testing problem, sufficient statistics
- Parallelism to estimation theory, composite detection problem
- Uni‐and multivariate Gaussian distribution, complex Gaussian and circular symmetry
- Continuous‐time stochastic processes
- Detection in white Gaussian noise
- Non‐coherent detection and nuisance parameters
In the second part of the course the following topics are covered:
- Signal detection in discrete time: Performance evaluation of procedures, e.g., Chernoff bound, sequential detection, non parametric and robust detection
- Elements of signal estimation
- Signal Detection in continuous time: The detection of deterministic and partly determined signals in Gaussian noise and the detection of random signals in Gaussian noise