EE 353, 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.