ECE 516: Adaptive Digital Filters

Prof. Mojtaba Soltanalian (msol@uic.edu)

 

Lectures & office hours

Lectures are given Tuesdays and Thursdays, 5:30-6:45pm in room 215 TH

Office hours: Thursdays 3:45-5:00pm, SEO 1031

 

Textbook and optional references

* Adaptive Filters, by Ali H. Sayed, John Wiley & Sons, NJ, 2008,

available in hard copy at the UIC Bookstore.

 

Other useful references:

- Simon Haykin, Adaptive Filter Theory, Fifth edition, Prentice Hall, 2013.

- Torsten Soderstrom, and Petre Stoica. System identification. Prentice-Hall, 1988. Available online: http://user.it.uu.se/~ps/sysidbook.pdf

 

Lectures

- The slides can be found here.

Date

To be covered

Further info.

8/23

Introduction to ECE 516

8/25

Basics- A Refresher

8/30

Mean-Square Error Estimation

9/1

Mean-Square Error Estimation

9/6

Linear Estimation

9/8

Linear Models and Applications

9/13

Linear Models and Applications
(P) Arindam Bose: Adaptive Imaging for Ground-Penetrating Radar

9/15

Constrained Estimation and Applications
(P) Lubna Shibly Mokatren: EEG Artifact Removal

9/20

Kalman Filtering
(P) Nishat Anjum Khan: Adaptive Kalman Filtering for Vehicle Navigation

9/22

Review Class

9/27

Midterm 1

9/29

Steepest-Descent Algorithms
(P) Paulito Mendoza: Denoising Nonlinear Time Series by Adaptive Filtering

10/4

Stochastic-Gradient Algorithms
(P) Rehan Khan: Adaptive Filtering for Hearing Aids

10/6

Other Local Algorithms

10/11

Least-Squares Methods

10/13

Recursive Least-Squares
(P) Rehan Khan: Sparse Channel Estimation with LMS

10/18

LS and RLS (continued)
(P) Prabhu Annabathula: LMS Adaption in Echo Cancelers

10/20

Review Class

10/25

Midterm 2

10/27

Guaranteed Adaptation
(P) Jacob Miller: Adaptive filtering to Predict Lung Tumor Motion; (P) Brook Feyissa: Adaptive Beam Forming Using a Cascade Configuration

11/1

Tracking Performance of Adaptive Filters
(P) Naveed Naimipour: Kalman Filtering for Highway Traffic Estimation

11/3

Tracking Performance of Adaptive Filters
(P) Chengyu Shi: Iterative Adaptive Approach for Blood Velocity Estimation

11/8

No classes.

11/10

Selected Topics (Large-Scale Adaptation and Big Data)

(P) Duc Vu: Recursive Least Squares Dictionary Learning Algorithm; (P) Shahin Khobahi: Distributed Kalman Filtering for Sensor Networks

11/15

Project Presentations

11/17

Project Presentations

11/22

Review Class

11/24

Thanksgiving holiday. No classes.

11/29

Project Presentations

12/1

Project Presentations

Final Exam Week 12/5 - 12/9


Course requirements and grading

Paper Presentations & Discussions 10%

Computer Project 15%

Homework 15%

Midterm exams 15% each

Final exam 30%

 

* An extra paper presentation for 10% bonus point may be accommodated. Prior consent from the instructor is required.

* These weights are approximate and may be subject to change.

* Late homework will not be accepted.

 

Homework (updated 10-19-2016)

HW1: out 9/9, due 9/15 -- problems I.10, I.11, I.12

HW2: out 9/9, due 9/27 -- problems II.1, II.20, II.24, II.34, II.37

HW3: out 10/19, due 10/25 -- problems III.1, III.3, VII.6(a), VII.35

HW4: out 11/29, due 12/09 -- problems IV.2(a)(b)(f), IV.10, IV.14, IV.15

 

Paper presentations

The presentations should be around 20-25 mins.

Some suggested papers can be found here.

 

Note

Students who wish to observe religious holidays should notify the instructor by the tenth day of the semester of the date when they will be absent unless the religious holiday is observed on or before the tenth day of the semester. In such cases, the students should notify the instructor at least five days in advance of the date when he/she will be absent. Every reasonable effort will be made to honor the request.

Academic dishonesty by students including plagiarism will result in appropriate disciplinary action. Intentional use or attempt to use unauthorized assistance, materials, information, or people in any examination, quiz, or assignment may lead to penalties such as a failing grade. College of Engineering and University guidelines will be followed.