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Article: Blind separation of electron paramagnetic resonance signals using diversity minimization
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TitleBlind separation of electron paramagnetic resonance signals using diversity minimization
 
AuthorsGuo, X1 2
Chang, C1
Lam, EY1
 
KeywordsBlind source separation
Diversity measures
Electron Paramagnetic Resonance spectroscopy
Non-negative sources
 
Issue Date2010
 
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/yjmre
 
CitationJournal Of Magnetic Resonance, 2010, v. 204 n. 1, p. 26-36 [How to Cite?]
DOI: http://dx.doi.org/10.1016/j.jmr.2010.01.014
 
AbstractThis paper presents a method for the blind separation of Electron Paramagnetic Resonance (EPR) spectroscopy signals that can aid in the detection of free radicals in living organisms. Observed EPR signals are often mixtures of source signals that are approximately "sparse", with a small number of narrow segments of the signal much larger than the remaining parts. We develop a method to separate the sources through minimizing a p-norm-like diversity measure under some mild assumptions which are generally valid for EPR signals. Simulations demonstrate that the proposed method performs well on EPR signal separation, with better robustness to noise compared to other techniques. © 2010 Elsevier Inc. All rights reserved.
 
ISSN1090-7807
2013 Impact Factor: 2.315
2013 SCImago Journal Rankings: 1.123
 
DOIhttp://dx.doi.org/10.1016/j.jmr.2010.01.014
 
ISI Accession Number IDWOS:000276785300004
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorGuo, X
 
dc.contributor.authorChang, C
 
dc.contributor.authorLam, EY
 
dc.date.accessioned2010-10-31T10:51:18Z
 
dc.date.available2010-10-31T10:51:18Z
 
dc.date.issued2010
 
dc.description.abstractThis paper presents a method for the blind separation of Electron Paramagnetic Resonance (EPR) spectroscopy signals that can aid in the detection of free radicals in living organisms. Observed EPR signals are often mixtures of source signals that are approximately "sparse", with a small number of narrow segments of the signal much larger than the remaining parts. We develop a method to separate the sources through minimizing a p-norm-like diversity measure under some mild assumptions which are generally valid for EPR signals. Simulations demonstrate that the proposed method performs well on EPR signal separation, with better robustness to noise compared to other techniques. © 2010 Elsevier Inc. All rights reserved.
 
dc.description.naturelink_to_subscribed_fulltext
 
dc.identifier.citationJournal Of Magnetic Resonance, 2010, v. 204 n. 1, p. 26-36 [How to Cite?]
DOI: http://dx.doi.org/10.1016/j.jmr.2010.01.014
 
dc.identifier.citeulike6862340
 
dc.identifier.doihttp://dx.doi.org/10.1016/j.jmr.2010.01.014
 
dc.identifier.epage36
 
dc.identifier.hkuros171687
 
dc.identifier.isiWOS:000276785300004
 
dc.identifier.issn1090-7807
2013 Impact Factor: 2.315
2013 SCImago Journal Rankings: 1.123
 
dc.identifier.issue1
 
dc.identifier.openurl
 
dc.identifier.pmid20194039
 
dc.identifier.scopuseid_2-s2.0-77950189509
 
dc.identifier.spage26
 
dc.identifier.urihttp://hdl.handle.net/10722/124738
 
dc.identifier.volume204
 
dc.languageeng
 
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/yjmre
 
dc.publisher.placeUnited States
 
dc.relation.ispartofJournal of Magnetic Resonance
 
dc.relation.referencesReferences in Scopus
 
dc.subject.meshBiopolymers - analysis - chemistry
 
dc.subject.meshComplex Mixtures - analysis - chemistry
 
dc.subject.meshComputer Simulation
 
dc.subject.meshElectron Spin Resonance Spectroscopy - methods
 
dc.subject.meshFree Radicals - analysis - chemistry
 
dc.subject.meshModels, Chemical
 
dc.subjectBlind source separation
 
dc.subjectDiversity measures
 
dc.subjectElectron Paramagnetic Resonance spectroscopy
 
dc.subjectNon-negative sources
 
dc.titleBlind separation of electron paramagnetic resonance signals using diversity minimization
 
dc.typeArticle
 
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Author Affiliations
  1. The University of Hong Kong
  2. University of Electronic Science and Technology of China