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Alternating strategies with internal ADMM for low-rank matrix reconstruction
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Medical Research Council, Imperial College London, White City, United Kingdom.
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-0355-2663
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-2638-6047
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2016 (English)In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 121, 153-159 p.Article in journal (Refereed) PublishedText
Abstract [en]

This paper focuses on the problem of reconstructing low-rank matrices from underdetermined measurements using alternating optimization strategies. We endeavour to combine an alternating least-squares based estimation strategy with ideas from the alternating direction method of multipliers (ADMM) to recover low-rank matrices with linear parameterized structures, such as Hankel matrices. The use of ADMM helps to improve the estimate in each iteration due to its capability of incorporating information about the direction of estimates achieved in previous iterations. We show that merging these two alternating strategies leads to a better performance and less consumed time than the existing alternating least squares (ALS) strategy. The improved performance is verified via numerical simulations with varying sampling rates and real applications.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 121, 153-159 p.
Keyword [en]
ADMM, Alternating strategies, Least squares, Low-rank matrix reconstruction
National Category
Control Engineering Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-180899DOI: 10.1016/j.sigpro.2015.11.002ISI: 000369193600013ScopusID: 2-s2.0-84949761064OAI: oai:DiVA.org:kth-180899DiVA: diva2:899484
Funder
Swedish Research Council, 621-2011-5847
Note

QC 20160202. QC 20160304

Available from: 2016-02-02 Created: 2016-01-25 Last updated: 2016-03-04Bibliographically approved

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