The following is taken directly from the Electrical
Engineering Department web site:
EE 317, Continuous- and Discrete-time Signals and
Systems, is a core course taken by all computer
engineering students that provides exposure to a variety of
topics in linear systems. The material in this course is
needed for further study in image processing and data
communications, both of which are major areas of
specialization within the computer engineering curriculum.
This course is divided into three main sections -
continuous-time linear system analysis, sampling and
reconstruction, and discrete-time (digital) linear system
analysis. Although the material covered in the first and last
sections is similar, fundamental differences between
continuous- and discrete-time exist. One of the goals of
this course is to make the student aware of these
differences.
The first part of the course discusses continuous-time
linear system analysis. It begins with basic time-domain
mathematical descriptions of various signals and systems.
The bulk of the analysis, however, is in frequency domain
approaches such as the Fourier Series and the Fourier
Transform. Applications such as modulation and
multiplexing are understood much easier using
frequency-domain analysis approaches.
The middle part of the course deals with the bridge
between continuous- and discrete-time, namely signal
sampling and reconstruction. Theoretical and practical
approaches to sampling/reconstruction are covered.
Finally the Nyquist sampling theorem, which is the key to
all digital signals, is developed. At this point, students are
ready to study discrete-time systems.
The final part of this course revisits system analysis,
although now discrete-time (or digital) systems are
considered. As in the continuous-time case, both
time-domain and frequency-domain approaches to the
analysis problem are discussed. The course ends with
select topics in the z-transform, which is the digital
counterpart to the Laplace transform.
