Compressed Sensing is about understanding how to capture and compresse a signal with the possibility of reconstructing it efficiently.
In the context of our Master's degree Compressed Sensing course (given by our professor Guillaume Lecué) we studies one of the major and founding publication of the field of Compressed Sensing Robust uncertainties principles, exact reconstruction from highly incomplete frequency data published by Candès and Tao in 2006. This project aims to describe the most important results of the paper and to implement in a simple framework one of its main breakthrough.
You'll find a report and notebook.