On phase retrieval via matrix completion and the estimation of low rank PSD matrices
Optimization and Control
2020-01-29 v2
Abstract
Given underdetermined measurements of a Positive Semi-Definite (PSD) matrix of known low rank , we present a new algorithm to estimate based on recent advances in non-convex optimization schemes. We apply this in particular to the phase retrieval problem for Fourier data, which can be formulated as a rank 1 PSD matrix recovery problem. Moreover, we provide theory for how oversampling affects the stability of the lifted inverse problem.
Keywords
Cite
@article{arxiv.1907.09537,
title = {On phase retrieval via matrix completion and the estimation of low rank PSD matrices},
author = {Marcus Carlsson and Daniele Gerosa},
journal= {arXiv preprint arXiv:1907.09537},
year = {2020}
}