ECE
531: Detection and Estimation Theory
Prof. Mojtaba
Soltanalian, UIC
Course webpage: http://msol.people.uic.edu/ECE531
Popular science description: here and here!
Textbook and
optional references
* Fundamentals of Statistical Signal Processing, Volume 1: Estimation Theory, by Steven M. Kay, Prentice Hall, 1993, and (possibly)
* Fundamentals of Statistical Signal Processing, Volume 2: Detection Theory, by Steven M. Kay, Prentice Hall 1998,
available in hard copy at the UIC Bookstore.
The following online resources will be partly used in the class:
http://user.it.uu.se/~ps/sysidbook.pdf
http://user.it.uu.se/~ps/SAS-new.pdf
Other useful references:
- Harry L. Van Trees, Detection, Estimation, and Modulation Theory,
- H. Vincent Poor, Introduction to Signal Detection and Estimation
- Louis L. Scharf and Cedric Demeure, Statistical Signal Processing: Detection, Estimation, and Time Series Analysis
- Carl Helstrom,
Elements of Signal Detection and Estimation.
Lectures
- The slides can be found here.
|
Date |
To be covered |
Further info. |
|
1/10 |
Introduction to ECE 531 |
|
|
1/12 |
Basics- A Refresher |
|
|
1/17 |
Minimum Variance Unbiased Estimator (MVUE) |
|
|
1/19 |
Cramer-Rao Lower Bound (CRLB) |
|
|
1/24 |
CRLB / Linear Model |
|
|
1/26 |
General MVUE |
|
|
1/31 |
General MVUE |
|
|
2/2 |
Best Linear Unbiased Estimator (BLUE) |
|
|
2/7 |
Review Class |
|
|
2/9 |
Midterm 1 |
|
|
2/14 |
No Classes |
|
|
2/16 |
Maximum Likelihood (ML) Estimation |
|
|
2/21 |
ML Estimation |
|
|
2/23 |
Least Squares Estimation |
|
|
2/28 |
Bayesian Estimation |
|
|
3/2 |
Kalman Filtering |
|
|
3/7 |
Review Class |
|
|
3/9 |
Midterm 2 |
|
|
3/14 |
No Classes |
|
|
3/16 |
Detection Theory- Preliminaries |
|
|
3/21 |
Spring Break, No Classes |
|
|
3/23 |
Spring Break, No Classes |
|
|
3/28 |
Detection Theory- Preliminaries |
Deadline to select project topic |
|
3/30 |
Detection Theory- Deterministic Signals |
|
|
4/4 |
Detection Theory- Random Signals |
|
|
4/6 |
Selected Topics |
|
|
4/11 |
Selected Topics |
|
|
4/13 |
Review Class |
|
|
4/18 |
Project Presentations |
|
|
4/20 |
Project Presentations |
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|
4/25 |
Project Presentations |
|
|
4/27 |
Project Presentations |
|
|
Final Exam Week 5/1 - 5/5 |
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 1-23-2023)
HW1: out 1/23 due 2/7
-- Estimation Book, problems 1.4, 2.9, 2.11, 3.10, 3.11, 3.12
HW2: out 1/23 due 2/9
-- Estimation Book, problems 4.1, 4.2, 5.9, 6.6, 6.13
HW3: out 1/23 due 4/18
-- Detection Book, problems 3.8, 3.14, 4.1, 4.6
HW4: out 1/23 due 4/25
-- Detection Book, problems 4.10, 5.12, 5.13
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.