Course overview
This course builds upon foundational digital signal processing (DSP) knowledge and explores advanced DSP topics and applications. The course will cover topics such as discrete-time (DT) random processes, adaptive filtering, spectral estimation, DT filter implementation strategies, multi-rate signal processing and an introduction to multidimensional signal processing. Practical hands-on experience will be gained through computer labs and projects. This course is suitable for engineers with technical interests in sensor information processing, telecommunications and artificial intelligence.
Course learning outcomes
- Choose and apply suitable technique(s) to estimate the spectral density of discrete-time (DT) signals
- Formulate and solve adaptive filter problems, and implement solution for applications such as linear prediction, Wiener and least mean-square (LMS) filters
- Describe the concept of multi-rate signal processing and apply technique to solve problems requiring decimation and interpolation, multi-rate filters, and wavelet transforms
- Implement and critically evaluate DSP algorithms through completing computer-based experiments involving simulated and real data
Degree list
The following degrees include this course