The Compressive Processing (CP) paradigm is fundamentally interdisciplinary, with interplay between applied/pure mathematics and engineering serving to fertilize new researches opening new frontiers. The impact of CP goes far beyond compression and classical signal processing. Whenever acquiring/inverting data/information is difficult, dangerous, or expensive, CP allows to proceed with much less data/information than previously thought possible. Such a possibility has been rapidly exploited in several and different ranges of practical engineering problems almost always leading to striking results that significantly advanced the state-of-the-art.

The course is targeted to make attendees (i) understanding the basics of CP, (ii) learning the leading-edge and most recent advances on CP-based algorithms, while (iii) overviewing the most appealing applications of CP in advanced engineering fields. Applicative examples including exercises will corroborate the theoretical concepts, as well.

Course Topics

• Review of the basics and fundamentals of CP
• Compressive sampling: acquisition problem and incoherent sampling
• Compressive sensing: retrieval problem and sparse signal reconstruction
• Advanced CP-based sampling methodologies at the state-of-the-art
• Advanced CP-based retrieval methodologies at the state-of-the-art
• Engineering applications of CP: capabilities, limitations, and perspectives
• Applicative examples including exercises regarding specific engineering applications of CP sampling and CP retrieval methodologies