Compressive sensing is a new mathematical technique in signal processing. It enables, for example, optical, radar, MRI and X-ray imaging systems with limited capabilities in bandwidth or resolution to recover "natural" signals with high accuracy. As a consequence, new system architectures can be devised where standard regular sampling is not attainable due to sensor power consumption, size, cost, or technological limitations.
This graduate textbook provides detailed background for study and research in compressive sensing, including signal models, measurement schemes, recovery algorithms, highlighting recent theoretical results and showing a broad range of applications. Due to its background information and numerous practical applications, it is an ideal resource for researchers, graduate students and practitioners who want to join this exciting research area.
Conveys basic principles, limitations, and potential applications with a focus on many industrially relevant ones.
Strong improvements of standard technologies (such as MRI and radars) are presented.
Joachim Ender, Fraunhofer Institute for High Frequency Physics and Radar Techniques, Germany.