Several problems arising in electromagnetics can be directly formulated or suitably recast for
an effective solution within the compressive sensing (CS) framework. This has motivated a …

The emerging field of compressed sensing has potentially powerful implications for the
design of optical imaging devices. In particular, compressed sensing theory suggests that …

Synthetic aperture radar (SAR) image formation can be treated as a class of ill-posed linear
inverse problems, and the resolution is limited by the data bandwidth for traditional imaging …

This first chapter formulates the objectives of compressive sensing. It introduces the
standard compressive problem studied throughout the book and reveals its ubiquity in many …

Used to analyze the time-evolution of fluid flows, dynamic mode decomposition (DMD) has
quickly gained traction in the fluids community. However, the existing DMD literature focuses …

This article covers recent advances in the fusion of metasurface antenna design and
computational imaging (CI) concepts for the realization of imaging systems that are planar …

By leveraging metamaterials and compressive imaging, a low-profile aperture capable of
microwave imaging without lenses, moving parts, or phase shifters is demonstrated. This …

This article presents a survey of recent research on sparsity-driven synthetic aperture radar
(SAR) imaging. In particular, it reviews 1) the analysis and synthesis-based sparse signal …

In the past decade, sparse and low-rank recovery has drawn much attention in many areas
such as signal/image processing, statistics, bioinformatics, and machine learning. To …

The paper studies the problem of recovering a spectrally sparse object from a small number
of time domain samples. Specifically, the object of interest with ambient dimension n is …