The study of computer vision, graphics and robotics requires background in the concept of discrete signals, filtering, and elementary linear systems theory. Discrete signals are obtained by sampling continuous signals. Starting with a continuous time signal, students will review the concept of a discrete signal, the conditions under which a continuous signal is completely represented by its discrete version, and discuss the analysis and design of linear time-invariant systems. In particular, frequency selective filters in both discrete and continuous time domain will be developed. An accompanying lab will cover applications of the concepts covered in the lectures to practical problems such as speech and image processing.

The following topics will be covered:

1. Continuous and discrete time signals.
2. Linear time-invariant systems.
3. Fourier analysis in continuous time.
4. Fourier analysis in discrete time.
5. Sampling: Conversion of CT signals to DT signals.
6. Laplace transform for CT signals
7. Z transform for DT signals.
8. Linear feedback systems.
9. Design of continuous and discrete time frequency selective filters.

There are three supervised lab hours per week.

• Mohammad H. Sajjadieh
• Office: LAS 2052 (Lassonde Building formerly Computer Science & Engineering Building)
• Phone: (416) 736-2100 x. 70143
• Email: mohammad AT cse DOT yorku DOT ca

M. Mandal and A. Asif, Continuous-time and Discrete-time Signals and Systems, Cambridge University Press, 2007, ISBN-13: 978-0-521-85455-9

Tuesdays and Thursdays, 13:00-14:30 LSB 101

• Mondays: 14:30 - 17:30, CSE 3057
• Fridays: 13:30 - 16:30, CSE 3057

The course material and website is adapted from a previous section of the course taught by Prof. Amir Asif, York University.