ECE551 — Digital Signal Processing II

Course description

Graduate-level introduction to signal processing with emphasis on vector space methods and adaptive signal processing.

The course prerequisites are undergraduate level probability and DSP. The linear algebra content will be self-contained, though taught at a somewhat fast pace.

Tuesday and Thursday, 12:30–2:00pm, Online

Announcements

Office Hours Information here

Lecture recordings available here

Submit Homework on Compass

Homework 4 Solution PDF and code

Homework 5 Posted! PDF, Source

Lecture 10 Notes Available

Lecture 9 Notes Available

Homework 4 Modified PDF Here

Course Overview

This plan will be refined over time.

Time Topics Reading
Week 1 Vector Space, Hilbert Space, Linear Operators [VKG] 1, 2.2, 2.3
Week 2 Projections, Bases, DTFT, Numerical Issues [VKG] 2.4 - 2.6
Week 3 Discrete-Time Signals [VKG] 3
Week 4 Multirate and Filterbanks [VKG] 3.7, 7.2-7.4, Notes
Weeks 5-6 Continuous-Time, Sampling and Interpolation [VKG] 4,5
Weeks 6-7 Stochastic Processes [VKG] 3.8, 4.6
Weeks 7-8 Approximation, Splines [VKG] 6
Week 9 Midterm
Week 10-13 Special Topics/Adaptive Signal Processing Notes
Week 14 Fall Break
Weeks 15-16 Final Project Presentations N/A

Reading

Textbook

Alternative Linear Algebra Treatment

Grading

Detailed Syllabus

Week 1 (8/24 – 8/28): Introduction, vector spaces, Hilbert space, and Linear Operators

Week 2 (8/31 - 9/4): Projections (continued), Bases, Numerical Issues

Week 3 (9/7 - 9/11):

Week 4 (9/14 - 9/18):

Week 5 (9/21 - 9/25):

Week 6 (9/28 - 10/2):

Week 7 (10/5 - 10/9):

Week 8 (10/12 - 10/16):

Week 9 (10/19 - 10/23):

Week 10 (10/26 - 10/30):

Week 11 (11/2 - 11/6):

Week 12 (11/9 - 11/13):

Week 13 (11/16 - 11/20):

Week 14 (11/23 - 11/27):

Week 15 (11/30 - 12/4):

Week 16 (12/7 - 12/9):