Signal Reconstruction from Phase-only Measurements: Uniqueness Condition, Minimal Measurement Number and Beyond
Not on the map. Why?
Abstract (arXiv)
This paper studies the phase-only reconstruction problem of recovering a complex-valued signal x in mathbbCd from the phase of Ax where A is a given measurement matrix in mathbbCm× d. The reconstruction, if possible, should be up to a positive scaling factor. By using the rank of discriminant matrices, uniqueness conditions are derived to characterize whether the underlying signal can be uniquely reconstructed. We are also interested in the problem of minimal measurement number. We show that at least 2d but no more than 4d-2 measurements are needed for the reconstruction of all x∈mathbbCd, whereas the minimal measurement number is exactly 2d-1 if we pursue the recovery of almost all signals. Moreover, when adapted to the phase-only reconstruction of x∈ℝd, our uniqueness conditions are more practical and general than existing ones. Our theoretical results can be straightforwardly extended to affine phase-only reconstruction where the phase of Ax+b is observed for some b∈mathbbCm.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 8 Sep 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2026: 1.
1 paper.
- 2026Image Reconstruction from Phase with Untrained Neural Priors25 Sep 2026