Basic Information
- Course Code: EE 779
- Course Name: Advanced Topics in Signal Processing
- Course Offered In: 2022-‘23
- Semester Season: Spring
- Instructors: Prof. Satish Mulleti
- Prerequisites: EE 229 & EE 325 (soft)
- Difficulty (1 being easy and 5 being tough): 4
Course Content
The planned course content was very ambitious from the beginning with the prof. wishing to cover a diverse range of topics in signal processing, including spectral estimation, Optimal filters, adaptive filtering, beamforming, finite rate of innovation, multiband sampling, compressed sensing, and model-based machine learning. Due to the paucity of time, the later topics did not get covered in much depth.
Feedback on Lectures
Lectures were pretty fast-paced, and the slides were not well organized, thus making the course hard to follow, even if a single lecture was missed. Attending lectures was essential to the course, and the exams had direct questions from them. The classes could feel a bit overwhelming to the students due to the sheer amount of new content in the lectures. Hence, the course required a regular study of the concepts throughout the semester. The instructor was easily approachable for any doubts, though.
Feedback on Evaluations
Grading scheme was- Mid Sem: 20, End Sem 40, Project 20, and Assignments 20, The exams were totally based on the lectures and not very difficult. There were three coding assignments that were very tedious in nature and consumed a significant amount of time. The project was to be done in groups of three, and the groups were made by the instructor himself. It involved implementing and improving any one of the given papers. The only issue was that he most of the papers did not have any pre-existing publicly available implementations The instructor had high expectations from the students and was not satisfied with most of the projects, but the final grading was overall decent.
Study Material and Resources
Monsoon H Hayes- Statistical Digital Signal Processing and Modelling Stoica and Moses- Spectral Analysis of Signals Certain other papers on Compressed Sensing
Follow-up Courses
None, the course has some overlap with EE 679 (Speech Processing), but these two courses can be taken in any order.
Final Takeaway
Overall the course is useful for someone who is interested in signal processing. It gives an introduction to a lot of new signal-processing techniques and applications. However, the course does demand significant effort and time commitment and also expects the student to have a strong foundation in linear algebra and probability.