A flexible convex relaxation for phase retrieval (Q1688995)

The paper under review deals with the problem of recovering a signal from noisy phaseless measurements with given measurement vectors. The authors propose a convex relaxation for the phase retrieval problem, which produces accurate solutions and is scalable. Compared to the non-convex phase retrieval methods, their approach inherits the flexibility of complex optimization both in analysis and application. Namely, it is demonstrated how sparsity constraints can be incorporated into the recovery algorithm. The effectiveness of the proposed method is illustrated through numerical simulations using both independent random measurements and coded diffraction patterns.