with Applications in Signal Processing and Pattern Recognition |

"It is vain to do with more what can be done with less." ---- William of Ockham

- October 23: There will be no lecture on Tuesday, October 28. Please use the time to work on your final project. The TA, John, will be teaching the lecture on Thursday, Octorber 30. He will start talking about applications.
- October 7: Two more handouts are given on matrix rank minimization.
- September 29: A few handouts on almost Euclidean sections of L1 ball and related papers are posted below. There will be no lecture on Thursday. You need to work on your midterm project proposal. It is due on October 9th. Please turn in your proposal by Wednesday the 8th by email in pdf format, and prepare a short presentation, 5 minutes, for the class on Thursday the 9th.
- September 15: A few more handouts are posted below. There will be no TA office hour this week.
- September 6: Homework 1 is assigned below and due on Tuesday, September 16.
- August 25: Welcome to ECE598YM, Fall 2008.

Lectures: Tuesday & Thursday 10:30am-11:50am, 170 Everitt Lab

Office hours: Tu 1:30pm-3:00pm, 145 Coordinated Science Lab

Office: 145 CSL, Phone: 244-0871

Email: yima@uiuc.edu

After hour appointments: through email.

Teaching Assistant: John Wright

Office hours: Friday 2-3pm, 146 Coordinated Science Lab

Email: jnwright@uiuc.edu

- Lectures on Discrete Geometry, Jiri Matousek, Springer, 2002.
- Convex Polytope, Branko Grunbaum, Springer, 2002.

This course covers recent developments of the new mathematical theory of sparse representation and compressed sensing in statistical signal processing, especially the concepts and results that can be readily applied to pattern recognition, computer vision, and signal (image, speech) processing. As this is a fastly evolving aera, it is my intension to study these new results together with all of the participants throughout the semester. So you do not have to be afraid that you do not know much about this topic, because neither do I.

- Notes and papers to be presented and discussed will be selected mainly from the Compressive Sensing Resources: Compressive Sensing Repository (maintained at Rice University).
- You may find some of my recent work related to this topic and other applications: Face Recognition via Sparse Representation.

- Homework One, assigned on September 6th and due on September 16th.

Yi Ma | yima@uiuc.edu