Event Date Details:
refreshments served at 3:15 p.m
- South Hall 5607F
- Department Seminar Series
Title: Fast and Robust Compressive Phase Retrieval Using Sparse-Graph Codes
Abstract: In this talk, we consider the problem of compressive phase retrieval that emerges in different applications such as optics, X-ray crystallography, astronomy, etc. The compressive phase retrieval problem is to recover a sparse complex signal from the magnitude of linear measurements. We consider two scenarios where the measurements are noiseless or noisy, and using coding theoretic tools, we develop the "PhaseCode" algorithm that has near-optimal sample and decoding complexity in both settings. Further, we provide extensive simulations results that show tight agreement between theory and practice. Finally, we will briefly discuss how our coding theoretic framework can tackle other sparse recovery problems such as sparse mixed linear regression, group testing, and sparse covariance estimation.