EE 313: Linear Signals and Systems
Signal processing is rich with tools that have applications in a broad class of problems including communications, controls, image compression, sonar, radar, array processing, and digital video. The theory is both elegant and beautiful. This course will be your first introduction to the concepts of signal processing, especially processing signals with linear systems. Although this course will often seem abstract, e.g. it consists mainly of mathematical models engineers use when designing systems, the tools you learn in this course will have practical application to many areas of engineering. Most directly the concepts can be applied to everyday problems like audio signal processing, e.g. processing speech and music, and image processing, e.g. photoshoping your favorite picture. You will find these show up again and again in your further education, especially if you pursue a specialization in communications, signal processing, systems, control theory, circuit design, and biomedical engineering among others By the end of this course you should be able to:
- Compute a system output in either time or frequency given the system input and a description of the system, using the Laplace, Fourier, or Z-transform, as appropriate.
- You should understand the differences and similarities between discrete and continuous time signals and systems.
- You should be able to create discrete signals by sampling continuous signals, and understand the requirements on the sampling.
Detailed powerpoint lectures notes were developed for Spring 2015. They are currently being revised for Fall 2015.
Electronic Course Site
All of the course details may be found on Canvas.
Signal Processing at UT Austin
- Wireless Networking and Communications Group
- Embedded Signal Processing Laboratory
- Laboratory for Image and Video Engineering
Signal Processing Links