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ECE 516: Adaptive Digital Filters

Prof. Mojtaba Soltanalian (msol@uic.edu)

 

Course Website

http://msol.people.uic.edu/ECE516

 

Lectures & office hours

Lectures are given Tuesdays and Thursdays, 5:30-6:45pm in room A5 LC

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.

8/29

Introduction to ECE 516

8/31

Basics- A Refresher

9/5

Mean-Square Error Estimation

9/7

Mean-Square Error Estimation

9/12

Linear Estimation

9/14

Linear Models and Applications

9/19

Linear Models and Applications
(P) Alberto Gianelli: Adaptive Filtering for Music/Voice Separation

9/21

Constrained Estimation and Applications
(P) Matthew Klug: Adaptive Microwave Imaging for Early Breast Cancer Detection

9/26

Kalman Filtering

9/28

Review Class

10/3

Midterm 1

10/5

Steepest-Descent Algorithms
(P) Lakshmi Sridevi: Kalman Filtering for Highway Traffic Estimation

10/10

Stochastic-Gradient Algorithms

10/12

Other Local Algorithms

10/17

Least-Squares Methods
(P) Hanyu Lin: Distributed Kalman Filtering for Sensor Networks

10/19

Recursive Least-Squares
(P) Srikanth Ramakrishna: ECG Noise Removal via Adaptive Filtering

10/24

LS and RLS (continued)
(P) Giri Balasubramanian: Removal of Ocular Artifacts from EEG by Adaptive Filtering

10/26

Review Class 

10/31

Midterm 2

11/2

Guaranteed Adaptation
(P) Krunal Parmar: Adaptive Filtering for Intelligent Speech Sensing----------------(P) Andrew Dwinal: Adaptive Kalman Filtering for Vehicle Navigation -----------(*) Deadline to select project topic

11/7

Tracking Performance of Adaptive Filters
(P) Tumin Wu: Robust Speech Recognition via Adaptive Filtering

11/9

Tracking Performance of Adaptive Filters
(P) Yu Guo: Earthquake Shakes Twitter Users; Real-Time Event Detection by Social Sensors

11/14

No classes

11/16

No classes

11/21

Selected Topics (Large-Scale Adaptation and Big Data)

11/23

Thanksgiving holiday. No classes. 

11/28

Review Class

11/30

Project Presentations

12/5

Project Presentations

12/7

Project Presentations

Final Exam Week 12/11 - 12/15


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 9-22-2017)

HW1: out 9/22 due 9/28 -- Adaptive Filters (textbook), problems I.10, I.11, I.12

HW2: out 9/22 due 10/3 -- Adaptive Filters (textbook), problems II.1, II.5, II.24, II.37

HW3: out 10/23 due 10/31 -- Adaptive Filters (textbook), problems III.1, III.3, VII.6(a), VII.35

 

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.