Phaseless Subspace Tracking
Machine Learning
2018-09-13 v1 Information Theory
math.IT
Machine Learning
Abstract
This work takes the first steps towards solving the "phaseless subspace tracking" (PST) problem. PST involves recovering a time sequence of signals (or images) from phaseless linear projections of each signal under the following structural assumption: the signal sequence is generated from a much lower dimensional subspace (than the signal dimension) and this subspace can change over time, albeit gradually. It can be simply understood as a dynamic (time-varying subspace) extension of the low-rank phase retrieval problem studied in recent work.
Cite
@article{arxiv.1809.04176,
title = {Phaseless Subspace Tracking},
author = {Seyedehsara Nayer and Namrata Vaswani},
journal= {arXiv preprint arXiv:1809.04176},
year = {2018}
}
Comments
To be appeared in GlobalSIP 2018