3480
University Street, Montreal, Quebec, CANADA
McGill University
Department of Electrical and Computer Engineering
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ECSE-621B STATISTICAL DETECTION AND ESTIMATION
Winter 2013
General Information:
Instructor:
Prof. H. Leib, Tel. 398-8938, room MC757
email : harry.leib@mcgill.ca
office hours : Thursday 15:00 -16:30
Teaching Assistant
TBD
TBD
TBD
Text book:
H. Vincent Poor, An Introduction to Signal Detection and Estimation, 2'nd edition, Springer-Verlag 1994
References:
Harry L. Van Trees, Detection, Estimation, and Modulation Theory, Part 1, Wiley 1968 (reprinted version)
Papers from technical journals
Final mark composition:
Assignments (20%), one midterm (2h, open books, 30%), term project (50%)
Schedule/Location:
Tuesday and Thursday, 11:35-12:55, room ENGTR2120
First Class:
Tuesday, Jan. 8, 2013
Term project:
The term projects are done by each student individually. The subject can be selected by the students ; however it requires the agreement of the instructor. The deliverable is a project report of 20-25 pages excluding figures and tables. Project Guidelines :
Milestones for term project:
Submission of title and 300 words abstract - Feb. 5, 2013
Submission of final paper - April 9, 2013 after the lecture.
Course Outline
The subject of Statistical Detection and Estimation lies at the intersection of telecommunication systems engineering, signal processing,
and mathematical statistics. It provides analytical tools for the analysis and synthesis of telecommunication and signal processing systems.
This subject has many applications in other areas too, such as : control, computer science, and bioengineering. The main objective of this
course is to provide a solid foundation, enabling students to apply such statistical tools in their own research. This course covers the
following main topics:1) Classical detection and estimation theory:
- Hypothesis testing (Neyman-Pearson and Bayes criteria), Minimax hypothesis testing
- Estimation theory (maximum-likelihood, maximum a-posterior, minimum mean-square error), Performance bounds
- Composite hypothesis testing, Generalized likelihood
2) Applications for discrete time signals in noise:
- Detection of signals in noise
- Estimation of signal parameters
- Detection of signals with nuisance parameters
3) Estimation of discrete time signals:
- Linear filtering
- Wiener filtering
- Kalman filtering
4) Discrete representation of continuous-time signals:
- Signal space concepts
- Karhunen-Loeve expansion of random processes
5) Detection and estimation of continuous time signals in noise:
- Detection of deterministic signals in noise
- Detection of random signals in noise
- Estimator-correlator structures
Announcements
TERM TEST
Type of exam :
Open books, open notes, all calculators allowed
Portable computers are not allowed Documents containing solutions to problems in the text book are not allowed.Date and Time :
Monday, March 25, 2013, 14:35-16:25
Location :
EDUC 433 (Education building room 433)
Material :
1) Class lectures from the beginning of the term and until March 19, 2013
2) Text book (Poor): pp. 1-97, p.141, pp. 157-158, pp. 169-181
Useful Links
Virtual lab on probability and statistics