The goal of this class is to present signal processing tools from an intuitive geometric point of view which is at the heart of all modern signal processing techniques from Fourier transforms and sampling theorems to time-frequency analysis and wavelets. The course is designed to provide the mathematical depth and rigor needed for the study of advanced topics in signal processing and also features introductions to current applications where such tools are crucial. In particular, several applications will be studied, including image compression with linear and non-linear approximation, array signal processing , mobile sensing, and prediction of the stock market.
During this course, students will:
- Master the right tools to tackle advanced signal and data processing problems
- Have an intuitive understanding of signal processing through a geometrical approach
- Get to know the applications that are of interest today
- Learn about topics that are at the forefront of signal processing research
- Professor: Julien René Pierre Fageot
- Teacher: Eric Bezzam
- Teacher: Sepand Kashani
