Phase recovery from a Bayesian point of view: the variational approach

Autor:	Drémeau, Angélique, Krzakala, Florent
Rok vydání:	2014
Předmět:	Computer Science - Information Theory Mathematics - Statistics Theory Statistics - Applications
Zdroj:	Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on Year: 2015 Pages: 3661- 3665
Druh dokumentu:	Working Paper
DOI:	10.1109/ICASSP.2015.7178654
Popis:	In this paper, we consider the phase recovery problem, where a complex signal vector has to be estimated from the knowledge of the modulus of its linear projections, from a naive variational Bayesian point of view. In particular, we derive an iterative algorithm following the minimization of the Kullback-Leibler divergence under the mean-field assumption, and show on synthetic data with random projections that this approach leads to an efficient and robust procedure, with a good computational cost. Comment: To appear in the proceedings of IEEE Int'l Conference on Acoustics, Speech and Signal Processing (ICASSP)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1410.1368 Zobrazit plný text záznamu View this record from Arxiv