| Credits | 4 |
|---|---|
| Tags | Signals Probability |
| Key Topics | Markov Chains, Filtering, Martingales, Diffusion |
| Prerequisites | ECE 2720, ECE 3100, and ECE 3250 or equivalents. |
| Course Tags | Last offered: FA25 |
This course provides an introduction to models for random signals in discrete and continuous time, Markov chains, Poisson process, queuing processes, power spectral densities, Gaussian random process, response of linear systems to random signals, and elements of estimation and inference as they arise in communications and digital signal processing systems.
Semester(s): Fall
Difficulty: N/A
Rating: N/A
Assignments: Seven homework sets.
Exams: One final exam.