🗜️ Compressed Sensing: Sparsity and the l1-norm
Table of Contents 1. Data compression 2. Compressed sensing 2.1. Problem formulation 2.2. When is it supposed to work? 2.3. The Restricted Isometry Property (RIP) 3. Why does the L1- norm work? 4. Conclusion 5. References In this series we will focus on the topic of Compressed Sensing. We will start by motivating the interest in this recent field. Sparse signals are ubiquitous in nature, and the ability to recover them from a small number of measurements has a wide range of applications....