Robust Sparse Phase Retrieval Made Easy

Abstract

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 measurement noise. In addition, the proposed strategy is fairly general, allowing for a large number of new measurement constructions and recovery algorithms to be designed with minimal effort.

References in corpus (2)

• Sparse Phase Retrieval: Convex Algorithms and Limitations
• Fast Compressive Phase Retrieval from Fourier Measurements

Cited by in corpus (1)

• Denoising Poisson Phaseless Measurements via Orthogonal Dictionary Learning