Fast Phase Retrieval from Localized Time-Frequency Measurements

Series
Applied and Computational Mathematics Seminar
Time
Monday, March 26, 2018 - 1:55pm for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Mark Iwen – Michigan State University – iwenmark@msu.eduhttp://users.math.msu.edu/users/markiwen/
Organizer
Wenjing Liao
We propose a general phase retrieval approach that uses correlation-based measurements with compactly supported measurement masks. The algorithm admits deterministic measurement constructions together with a robust, fast recovery algorithm that consists of solving a system of linear equations in a lifted space, followed by finding an eigenvector (e.g., via an inverse power iteration). Theoretical reconstruction error guarantees are presented. Numerical experiments demonstrate robustness and computational efficiency that outperforms competing approaches on large problems. Finally, we show that this approach also trivially extends to phase retrieval problems based on windowed Fourier measurements.