Enter the world of signal processing: analyze and extract meaning from the signals around us!
Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, re-mixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires real-world data to be captured by a computer and then manipulated digitally to extract the salient information. Ever wonder how signals from the physical world are sampled, stored, and processed without losing the information required to make predictions and extract meaning from the data?
Students will find out in this rigorous mathematical introduction to the engineering field of signal processing: the study of signals and systems that extract information from the world around us. This course will teach students to analyze discrete-time signals and systems in both the time and frequency domains. Students will learn convolution, discrete Fourier transforms, the z-transform, and digital filtering. Students will apply these concepts in interactive MATLAB programming exercises (all done in browser, no download required).
Prerequisites include strong problem solving skills, the ability to understand mathematical representations of physical systems, and advanced mathematical background (one-dimensional integration, matrices, vectors, basic linear algebra, imaginary numbers, and sum and series notation). This course is an excerpt from an advanced undergraduate class at Rice University taught to all electrical and computer engineering majors.
Before your course starts, try the new edX Demo where you can explore the fun, interactive learning environment and virtual labs. Learn more.
Professor Richard G. Baraniuk grew up in Winnipeg, Canada, the coldest city in the world with a population over 600,000. He studied Electrical Engineering at the Unviersity of Manitoba, the University of Wisconsin-Madison, and the University of Illinois at Urbana-Champaign. Dr. Baraniuk joined Rice University in Houston, Texas, in 1993 and is now the Victor E. Cameron Professor of Electrical and Computer Engineering. He is a member of the Digital Signal Processing (DSP) group and Director of the Rice center for Digital Learning and Scholarship (RDLS). Dr. Baraniuk’s research interests lie in the areas of signal, image, and information processing and include machine learning and compressive sensing. He is Director of Connexions, a non-profit publishing project to bring learning materials to the Internet Age which is used by over 2 million people from nearly 200 countries.