On phase retrieval via matrix completion and the estimation of low rank PSD matrices
Research output: Contribution to journal › Article
Given underdetermined measurements of a positive semi-definite (PSD) matrix X of known low rank K, we present a new algorithm to estimate X 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 a theory for how oversampling affects the stability of the lifted inverse problem.
|Research areas and keywords||
Subject classification (UKÄ) – MANDATORY
|Publication status||Published - 2020|