Please use this identifier to cite or link to this item: https://doi.org/10.1002/jcc.10080
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dc.titlePure component spectral reconstruction from mixture data using SVD, global entropy minimization, and simulated annealing. Numerical investigations of admissible objective functions using a synthetic 7-species data set
dc.contributor.authorWidjaja, E.
dc.contributor.authorGarland, M.
dc.date.accessioned2014-10-09T09:59:49Z
dc.date.available2014-10-09T09:59:49Z
dc.date.issued2002-07-15
dc.identifier.citationWidjaja, E., Garland, M. (2002-07-15). Pure component spectral reconstruction from mixture data using SVD, global entropy minimization, and simulated annealing. Numerical investigations of admissible objective functions using a synthetic 7-species data set. Journal of Computational Chemistry 23 (9) : 911-919. ScholarBank@NUS Repository. https://doi.org/10.1002/jcc.10080
dc.identifier.issn01928651
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/92292
dc.description.abstractA combination of singular value decomposition, entropy minimization, and simulated annealing was applied to a synthetic 7-species spectroscopic data set with added white noise. The pure spectra were highly overlapping. Global minima for selected objective functions were obtained for the transformation of the first seven right singular vectors. Simple Shannon type entropy functions were used in the objective functions and realistic physical constraints were imposed in the penalties. It was found that good first approximations for the pure component spectra could be obtained without the use of any a priori information. The present method out performed the two widely used routines, namely Simplisma and OPA-ALS, as well as IPCA. These results indicate that a combination of SVD, entropy minimization, and simulated annealing is a potentially powerful tool for spectral reconstructions from large real experimental systems.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/jcc.10080
dc.sourceScopus
dc.subjectEntropy minimization
dc.subjectGlobal optimization
dc.subjectPure component spectral reconstruction
dc.subjectSimulated annealing
dc.subjectSingular value decomposition
dc.typeArticle
dc.contributor.departmentCHEMICAL & ENVIRONMENTAL ENGINEERING
dc.description.doi10.1002/jcc.10080
dc.description.sourcetitleJournal of Computational Chemistry
dc.description.volume23
dc.description.issue9
dc.description.page911-919
dc.description.codenJCCHD
dc.identifier.isiut000175774100006
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