English

Phase retrieval from very few measurements

Functional Analysis 2013-07-30 v1 Computational Complexity Information Theory math.IT

Abstract

In many applications, signals are measured according to a linear process, but the phases of these measurements are often unreliable or not available. To reconstruct the signal, one must perform a process known as phase retrieval. This paper focuses on completely determining signals with as few intensity measurements as possible, and on efficient phase retrieval algorithms from such measurements. For the case of complex M-dimensional signals, we construct a measurement ensemble of size 4M-4 which yields injective intensity measurements; this is conjectured to be the smallest such ensemble. For the case of real signals, we devise a theory of "almost" injective intensity measurements, and we characterize such ensembles. Later, we show that phase retrieval from M+1 almost injective intensity measurements is NP-hard, indicating that computationally efficient phase retrieval must come at the price of measurement redundancy.

Keywords

Cite

@article{arxiv.1307.7176,
  title  = {Phase retrieval from very few measurements},
  author = {Matthew Fickus and Dustin G. Mixon and Aaron A. Nelson and Yang Wang},
  journal= {arXiv preprint arXiv:1307.7176},
  year   = {2013}
}

Comments

18 pages, 1 figure

R2 v1 2026-06-22T00:58:43.031Z