Compressive sensing (CS) is a fundamentally interdisciplinary topic, with interplay between applied/pure mathematics and engineering serving to fertilize innovative researches opening new frontiers. The impact of CS goes far beyond compression and classical signal processing. Whenever acquiring/inverting data/information is difficult, dangerous, or expensive, it is possible 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 electromagnetic problems almost always leading to striking results that significantly advance the state‐of‐the‐art.
This course, after reviewing the fundamentals of Compressive Sensing, will focus on classical and recently introduced solution procedures and algorithms, discussing the capabilities, the limitations, and the perspectives of CS in antenna design, imaging, non-destructive testing, and sensing and diagnosis applications.
The course is targeted to PhD students, Researchers, Scientists, and Engineers who are willing to (a) learn about the basics of Compressive Sensing; (b) enhance their background on CS in electromagnetics; (c) know about the leading edge and more recent advances on CS algorithms as applied to ill-posed synthesis and inverse problems; (d) take an overview on the applications of Compressive Sensing in academic and industrial frameworks.
- Day 1: Introduction and Basic Theory of CS
- Day 2: CS in Antenna Design and Engineering
- Day 3: Applications of CS in Antenna Characterization and Diagnosis
- Day 4: CS in Inverse Problems and Imaging
- Day 5: Further Applications & Advanced Topics in CS