In this short note we propose a simple two-stage sparse phase retrieval strategy that uses a
near-optimal number of measurements, and is both computationally efficient and robust to …

The problem of signal recovery from its Fourier transform magnitude is of paramount
importance in various fields of engineering and has been around for more than 100 years …

We propose a flexible convex relaxation for the phase retrieval problem that operates in the
natural domain of the signal. Therefore, we avoid the prohibitive computational cost …

In this paper, we consider the problem of estimating simultaneously low-rank and row-wise
sparse matrices from nested linear measurements, where the linear operator consists of the …

The problem of sparse phase retrieval is considered where the measurement vectors are
deterministic and Fourier-like. Under some mild assumptions, O (slog N) measurements are …

The problem of sparse phase retrieval is considered where the goal is to recover a sparse
complex valued vector (with s non zero elements) from the magnitudes of its linear …

Modulated wideband converters are now a well established sampling schemes to acquire
samples of sparse multiband signals with a sub-Nyquist sampling rate such that the signal …

In this paper, we tackle the general compressive phase retrieval problem. The problem is to
recover (to within a global phase uncertainty) a K-sparse complex vector of length n, x∈ ℂ n …

Sub-Nyquist sampling has received a huge amount of interest in the past decade. In
classical compressed sensing theory, if the measurement procedure satisfies a particular …

Compressed covariance sensing using quadratic samplers is gaining increasing interest in
recent literature. Covariance matrix often plays the role of a sufficient statistic in many signal …