University of Toronto
Department of Electrical & Computer Engineering
Communications Group

ECE 1511S, Spring 2009

Signal Processing

Course URL:http://portal.utoronto.ca/...
Class Notes for all lectures will be distributed. The notes will be available on line and can be downloaded from the course website.
Instructor: Prof. D. Hatzinakos
BAHEN BUILDING, 40 St George Str., Room 4144
Tel: 978-1613, E-mail: dimitris@comm.toronto.edu
Overview: The course deals with some basic and some advanced topics in the area of digital signal processing. Emphasis is given to statistical signal processing with applications.
Text: D. Manolakis, V. Ingle and S. Kogon, Statistical and adaptive signal processing, Artech House, 2005
OTherRecommended references: 1. Monson Hayes,Statistical Digital Signal Processing and Modeling, Wiley, 1996
2. Charles W. Therrien, Discrete Random Signals and Statistical Signal Processing, Prentice Hall, 1992
Grading:
One to two problems or computer exercises will be assigned during each lecture. 
A report is due a week later: 50%(presentation: 15%, final report: 35%)
A common project will be assigned by the end of September. Students are expected to make a presentation on their approach and methodology to address the assigned project during the last two lectures. Interactive discussion and feedback from the class is expected. Final project reports are due on Dec. 15.
Place and Time:
BA4164 (BAHEN Building), Wednesdays, 1:00-3:00 (starting Jan. 14, 2009)
Office hours:Mondays 2:30-3:30 pm

Tentative Course plan

Jan. 14 Introduction, Discrete Signal Processing and Linear Algebra fundamentals
From text: Chapter 2 (2.1-2.3), Appendices A,B
Lecture 1 , Problem set 1,
Jan. 21 Discrete time random processes and linear filtering
Lecture 2
Jan. 28 Discrete time random processes and linear filtering (continued)
Lecture 3
Feb. 4 Discrete signal modeling and statistical signal processing
Feb. 11 MSE and Wiener Filtering>
Feb. 18 Reading week. Heart-sound data recording session (BA7129)
Feb. 25 Kalman Filtering,
March 4 Adaptive systems and algorithms (LMS, RLS),
March 11 Spectrum Estimation,
March 18 Spectrum Estimation (continued),
March 25 Array Processing,
April 1 TBD
April 8 Presentation of course projects
April 15 Presentation of course projects
April 22 Deadline for project reports