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Pregled bibliografske jedinice broj: 393585

Multi-component Analysis: Blind Extraction of Pure Components Mass Spectra using Sparse Component Analysis


Kopriva, Ivica; Jerić, Ivanka
Multi-component Analysis: Blind Extraction of Pure Components Mass Spectra using Sparse Component Analysis // Journal of mass spectrometry, 44 (2009), 9; 1378-1388 doi:10.10002/jms.1627 (međunarodna recenzija, članak, znanstveni)


Naslov
Multi-component Analysis: Blind Extraction of Pure Components Mass Spectra using Sparse Component Analysis

Autori
Kopriva, Ivica ; Jerić, Ivanka

Izvornik
Journal of mass spectrometry (1076-5174) 44 (2009), 9; 1378-1388

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Mass spectrometry ; Chemometrics ; Blind source separation ; Sparse component analysis ; Nonnegative matrix factorization.

Sažetak
The paper presents sparse component analysis (SCA)-based blind decomposition of the mixtures of mass spectra into pure components, wherein the number of mixtures is less than number of pure components. Standard solutions of the related blind source separation (BSS) problem that are published in the open literature require the number of mixtures to be greater than or equal to the unknown number of pure components. Specifically, we have demonstrated experimentally the capability of the SCA to blindly extract five pure components mass spectra from two mixtures only. Two approaches to SCA are tested: the first one based on norm minimization implemented through linear programming and the second one implemented through multilayer hierarchical alternating least square nonnegative matrix factorization with sparseness constraints imposed on pure components spectra. In contrast to many existing blind decomposition methods no a priori information about the number of pure components is required. It is estimated from the mixtures using robust data clustering algorithm together with pure components concentration matrix. Proposed methodology can be implemented as a part of software packages used for the analysis of mass spectra and identification of chemical compounds.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Kemija, Računarstvo



POVEZANOST RADA


Projekt / tema
098-0982903-2558 - Analiza višespektralih podataka (Ivica Kopriva, )
098-0982933-2936 - Kemijske preobrazbe prirodnih spojeva (Lidija Varga-Defterdarović, )

Ustanove
Institut "Ruđer Bošković", Zagreb

Citiraj ovu publikaciju

Kopriva, Ivica; Jerić, Ivanka
Multi-component Analysis: Blind Extraction of Pure Components Mass Spectra using Sparse Component Analysis // Journal of mass spectrometry, 44 (2009), 9; 1378-1388 doi:10.10002/jms.1627 (međunarodna recenzija, članak, znanstveni)
Kopriva, I. & Jerić, I. (2009) Multi-component Analysis: Blind Extraction of Pure Components Mass Spectra using Sparse Component Analysis. Journal of mass spectrometry, 44 (9), 1378-1388 doi:10.10002/jms.1627.
@article{article, year = {2009}, pages = {1378-1388}, DOI = {10.10002/jms.1627}, keywords = {Mass spectrometry, Chemometrics, Blind source separation, Sparse component analysis, Nonnegative matrix factorization.}, journal = {Journal of mass spectrometry}, doi = {10.10002/jms.1627}, volume = {44}, number = {9}, issn = {1076-5174}, title = {Multi-component Analysis: Blind Extraction of Pure Components Mass Spectra using Sparse Component Analysis}, keyword = {Mass spectrometry, Chemometrics, Blind source separation, Sparse component analysis, Nonnegative matrix factorization.} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


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