Signal processing is an invaluable tool in research. In turn signal processing is built upon effective models of signals and noise. Offered each year and addressing both modeling and signal processing, this course emphasizes the modeling one year and signal processing techniques the other.
The course introduces the modeling of signals and noise, considering concepts such as distributions and coherence. Examples are drawn from a wide range of bioengineering applications, from ultrasound through to fluorescent detection. Modeling of stochastic intracellular reactions/signals will also be considered. You will learn how to extract information from signals and will be able to place confidence measures on the results. The basics of detection and estimation theory are studied. There is a strong emphasis on classical techniques such as filtering, averaging, correlation, spectral estimation and conventional beamforming.Prerequisite is the equivalent of an undergraduate signals or control systems course. This course should be suitable for all engineers and physicists. IBBME students with life science backgrounds may also take the course and are encouraged to consult with the instructor.
Lectures: 10:00-13:00 Thursdays in Room 412, Rosebrugh Building, 4 Taddle Creek Rd. (First meeting is Jan 11th.)
Web site: www.ecf.utoronto/~sdavies/bme1452.html
Van Trees, H.L. "Detection, Estimation and Modulation Theory"
Announcements
Diary
Last year's web pages
Assignment 1
Assignment 2 dealt with describing signals subjectively and was given in
class.
Assignment 3
Assignment 4
Answers for Assignment 4
Style template for final paper (4 page IEEE conference style)
Instructor: Prof. Stephen W. Davies
stephen.davies@utoronto.ca
MSB 4226, 946-7176
Grading:
Assignments 15%
Mid-term paper 15%
Project 30%
Final 40%