Technical Talk : Compressive Sensing – Theory and Applications in Communications and Big Data | 17 May 2016

This tutorial covers theory and applications of compressive sensing to modern information processing systems, focusing on large-scale, distributed information processing and big data. The tutorial first gives a detailed overview of compressive sensing theory, including its motivations, the main theoretical results and the most significant application areas. Then, it surveys a few new applications to scenarios where compressive sensing can provide a significant performance boost. In particular, the tutorial will describe compressive sensing applications in the framework of low-power distributed systems and sensor networks, applications to big data including large-scale camera identification for image copyright protection in social media sites, the use of compressing sensing as an encryption layer, and the use of the sparsity model for indoors localization.