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Bayesian Cramer-Rao bounds for factorized model based low rank matrix reconstruction
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-6992-5771
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0003-2638-6047
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-6855-5868
2016 (English)In: 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), Institute of Electrical and Electronics Engineers (IEEE), 2016, 1227-1231 p.Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Low-rank matrix reconstruction (LRMR) problem considersestimation (or reconstruction) of an underlying low-rank matrixfrom under-sampled linear measurements. A low-rank matrix can be represented using a factorized model. In thisarticle, we derive Bayesian Cramer-Rao bounds for LRMR where a factorized model is used. We first show a general informative bound, and then derive several Bayesian Cramer-Rao bounds for different scenarios. We always considered the low-rank matrix to be reconstructed as a random matrix, but its model hyper-parameters for three cases - deterministic known, deterministic unknown and random. Finally we compare the bounds with existing practical algorithms through numerical simulations.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. 1227-1231 p.
Keyword [en]
Low-rank matrices, matrix completion, Bayesian estimation, Cramer-Rao bounds.
National Category
Signal Processing
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-190111ISI: 000391891900234Scopus ID: 2-s2.0-85005949749OAI: oai:DiVA.org:kth-190111DiVA: diva2:951514
Conference
24th European Signal Processing Conference (EUSIPCO), AUG 28-SEP 02, 2016, Budapest, HUNGARY
Note

QC 20160810

Available from: 2016-08-09 Created: 2016-08-09 Last updated: 2017-02-13Bibliographically approved

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fulltext(467 kB)34 downloads
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Sundin, Martin

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CiteExportLink to record
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Citation style
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