Signal recovery using expectation consistent approximation for linear observations

Yoshiyuki Kabashima, Mikko Vehkaperä

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

26 Citations (Scopus)

Abstract

A signal recovery scheme is developed for linear observation systems based on expectation consistent (EC) mean field approximation. Approximate message passing (AMP) is known to be consistent with the results obtained using the replica theory, which is supposed to be exact in the large system limit, when each entry of the observation matrix is independently generated from an identical distribution. However, this is not necessarily the case for general matrices. We show that EC recovery exhibits consistency with the replica theory for a wider class of random observation matrices. This is numerically confirmed by experiments for the Bayesian optimal signal recovery of compressed sensing using random row-orthogonal matrices.

Original languageEnglish
Title of host publication2014 IEEE International Symposium on Information Theory, ISIT 2014
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages226-230
ISBN (Print)978-1-4799-5186-4
DOIs
Publication statusPublished - 1 Jan 2014
MoE publication typeA4 Article in a conference publication
Event2014 IEEE International Symposium on Information Theory, ISIT 2014 - Honolulu, HI, United States
Duration: 29 Jun 20144 Jul 2014

Publication series

SeriesIEEE International Symposium on Information Theory. Proceedings
Volume2014
ISSN2157-8095

Conference

Conference2014 IEEE International Symposium on Information Theory, ISIT 2014
CountryUnited States
CityHonolulu, HI
Period29/06/144/07/14

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    Kabashima, Y., & Vehkaperä, M. (2014). Signal recovery using expectation consistent approximation for linear observations. In 2014 IEEE International Symposium on Information Theory, ISIT 2014 (pp. 226-230). [6874828] IEEE Institute of Electrical and Electronic Engineers. IEEE International Symposium on Information Theory. Proceedings, Vol.. 2014 https://doi.org/10.1109/ISIT.2014.6874828