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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.
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
2015 (English)In: Proceedings of the 24th European Signal Processing Conference (EUSIPCO), 2015, Institute of Electrical and Electronics Engineers (IEEE), 2015Conference paper, Poster (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), 2015.
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-190111OAI: oai:DiVA.org:kth-190111DiVA: diva2:951514
Conference
The 24th European Signal Processing Conference (EUSIPCO), 31st August to 4 of September 2015
Note

QC 20160810

Available from: 2016-08-09 Created: 2016-08-09 Last updated: 2016-08-10Bibliographically approved

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