Invertibility and Robustness of Phaseless Reconstruction
Functional Analysis
2013-08-23 v1 Computer Vision and Pattern Recognition
Machine Learning
Abstract
This paper is concerned with the question of reconstructing a vector in a finite-dimensional real Hilbert space when only the magnitudes of the coefficients of the vector under a redundant linear map are known. We analyze various Lipschitz bounds of the nonlinear analysis map and we establish theoretical performance bounds of any reconstruction algorithm. We show that robust and stable reconstruction requires additional redundancy than the critical threshold.
Cite
@article{arxiv.1308.4718,
title = {Invertibility and Robustness of Phaseless Reconstruction},
author = {Radu Balan and Yang Wang},
journal= {arXiv preprint arXiv:1308.4718},
year = {2013}
}
Comments
19 pages