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Self Modeling Curve Resolution
Abstract
This paper presents a method for determining the shapes of two overlapping functions f 1(x) and f 2(x) from an observed set of additive mixtures, [α i f 1(x) + β i f 2(x); i = 1, …, n), of the two functions. This type of problem arises in the fields of spectrophotometry, chromatography, kinetic model building, and many others. The methods described by this paper are based on the use of principal component techniques, and produce two bands of functions, each of which contains one of the unknown, underlying functions. Under certain mild restrictions on the fj (x), each band reduces to a single curve, and the fi (x) are completely determined by the analysis.
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Citations
Cited by
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Martens, H., & Geladi, P. (2004) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess1105 · Cited by 404
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Rosenthal, W., & Dozier, J. (1996) · Water Resources Research · doi:10.1029/95wr02718 · Cited by 295
Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry
Verbeeck, N., Caprioli, R. M., & Van de Plas, R. (2020) · Mass Spectrometry Reviews · doi:10.1002/mas.21602 · Cited by 281
Binding of divalent cations to acetate: molecular simulations guided by Raman spectroscopy
Mendes de Oliveira, D., Zukowski, S. R., Palivec, V., Hénin, J., Martinez-Seara, H., Ben-Amotz, D., Jungwirth, P., & Duboué-Dijon, E. (2020) · Physical Chemistry Chemical Physics · doi:10.1039/d0cp02987d · Cited by 73
Metadata
- Authors
- Lawton, W. H., & Sylvestre, E. A.
- Venue
- Technometrics
- Publisher
- Informa UK Limited
- Published
- 1971-08
- Volume
- 13
- Issue
- 3
- Pages
- 617-633
- ISSN
- 0040-1706 (ISSN-L)
- 1537-2723
- OpenAlex
- W1972326413
- Cited by
- 924
- References
- 0
- FWCI
- 9.17
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lawton, W. H., & Sylvestre, E. A. (1971). Self Modeling Curve Resolution. Technometrics. https://doi.org/10.1080/00401706.1971.10488823
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
