We address the waveform design problem for multiple-input multiple-output (MIMO) radar in
spectrally crowded environments. We exploit the mutual information between the target …

Multispectral cameras collect image data with a greater number of spectral channels than
traditional trichromatic sensors, thus providing spectral information at a higher level of detail …

One popular method for dealing with large-scale data sets is sampling. For example, by
using the empirical statistical leverage scores as an importance sampling distribution, the …

This paper presents a framework for compressed sensing that bridges a gap between
existing theory and the current use of compressed sensing in many real-world applications …

Compressive sensing of signals drawn from a Gaussian mixture model (GMM) admits closed-
form minimum mean squared error reconstruction from incomplete linear measurements. An …

A blind compressive sensing algorithm is proposed to reconstruct hyperspectral images from
spectrally-compressed measurements. The wavelength-dependent data are coded and then …

A Gaussian mixture model (GMM)-based algorithm is proposed for video reconstruction from
temporally compressed video measurements. The GMM is used to model spatio-temporal …

Compressive tomography consists of estimation of high-dimensional objects from lower
dimensional measurements. We review compressive tomography using radiation fields …

With the adoption of arbitrary and increasingly wideband signals, the design of modern
radar systems continues to be limited by analog-to-digital converter technology and data …

This Letter presents a compressive camera that integrates mechanical translation and
spectral dispersion to compress a multi-spectral, high-speed scene onto a monochrome …