EE 351 Signals and Systems

2010-2011

Website: http://www.engr.usask.ca/classes/EE/351/

Dr. David M. Klymyshyn

Office: 3B06 966-5393

Objective:

Understanding signals and systems and their representations in both the time and frequency domains is fundamental to Electrical Engineering. This course develops the student's understanding of mathematical transform techniques and their use in modeling the behavior of both analog and digital systems. It also develops the student's ability to apply system concepts and transform techniques in formulating and solving engineering problems. The tentative outline of the course is as follows.

Content (approximate and subject to change):

Fundamentals of Signals and Systems

Definition

Transformations of time

Exponential and sinusoidal signals

Unit Impulse and unit step functions

Continuous-time and discrete-time systems

Basic system properties

Linear Time-Invariant Systems

Convolution sum

Convolution integral

Properties of LTI systems

Fourier Series Representation of Periodic Signals

LTI System response to complex exponentials

Definition and properties of Fourier series

Convergence of the Fourier series

Representation of discontinuous signals

Discrete-Time Fourier Series (DTFS)

Continuous-Time Fourier Transform

Representation of the Fourier transform of aperiodic signals

Definition and properties of the continuous-time Fourier transform

The inverse Fourier transform, time-frequency duality, the uncertainty principle

Parseval's theorem

Example applications

Introduction to Communications

Complex exponential modulation

Sinusoidal amplitude modulation

Demodulation: synchronous & asynchronous

Frequency-division multiplexing

Sampling

Impulse-train sampling

Signal reconstruction by interpolation

The sampling theorem

Aliasing

Discrete-time processing of continuous-time signals

Discrete-Time Fourier Transform (time permitting)

Representation of aperiodic signals

Convergence of the DTFT

Fourier transform of periodic signals

Properties of the DTFT

The convolution property and its relationship to the DTFT

Relationship of FFT to DFT

Evaluation (suggested and subject to change):

Assignments 15 %

Midterm Exam (in class) 30 %

Final Exam 55 %

Text: Signals and Systems (2nd Ed) - Oppenheim, Willsky, Nawab