Welcome to **ECE551**, a graduate level course in digital signal processing, also known as DSP-II. In
this class we will cover advanced concepts in digital signal processing (e.g geometry and algebra of signals and systems
spaces, approximations, filtering etc.). The course prerequisites are undergraduate level probability and DSP (ECE313
and ECE310 or their equivalents). Background in Linear Algebra and Calculus is strongly recommended.

Homework will be given on a weekly basis.

- Submission Instruction in this link
- Homework 1 (due Sep. 11th) index_vector module
- Homework 2 (due Sep. 27th)
- Homework 3 (due Sep. 30th)

- Week #1: Lecture #1 slides (Monday), lecture #2 slides (Wednesday), Python notebook and audio file
- Week #3: Lecture #4 slides, complementary notes for Monday lecture (lecture #4), audio projections notebook and an example pulse, Radon transform notebook
- Week #3: Scribbles from the Radon lecture (to complement the Python notebook)
- Week #4: Lecture #6 slides (Monday), lecture #7 slides (Wednesday)

- Our textbook: "Foundations of Signal Processing" by Vetterli, Kovačević, and Goyal.
- Download Anaconda (Scientific Python). Python 3.6 is preferred.