Global least-squares analysis of large, correlated spectral data sets and application to chemical kinetics and time-resolved fluorescence

Review of Scientific Instruments

Volumn 67, Issue 12, 1996, Pages 4380-4386

  Stilbs, Peter ^a   Paulsen, Kim ^a  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

DATA STRUCTURES; EMISSION SPECTROSCOPY; FLUORESCENCE; FOURIER TRANSFORMS; LEAST SQUARES APPROXIMATIONS; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; REACTION KINETICS; SIGNAL TO NOISE RATIO;

BANDSHAPE; CORRELATED SPECTRAL DATA SETS; PULSED FIELD GRADIENT SPIN ECHO;

FORTRAN (PROGRAMMING LANGUAGE);

EID: 0030402985     PISSN: 00346748     EISSN: None     Source Type: Journal    
DOI: 10.1063/1.1147539     Document Type: Article

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12. At this stage we would like to draw the reader's attention to previous work by Kubista et al. (Refs. 13-15) that describes a multivariate statistical approach (NIPALS/Procrustean rotation) to some of the family of problems discussed here, that in principle does not require any such previous knowledge; the number of components, the bandshapes, and their amplitudes do become extracted directly. In order to achieve this, one needs to be able to compare the information in two data sets where the components have been attenuated differentially, by a preparatory experiment. Kubista et al. do describe a large number of such combinations of experiments in various types of optical spectroscopy. The method is unique, and very valuable in a case where one does not actually know the amplitude-(varied parameter) model or the number of components. However, the method is not at all as generally applicable as the CORE approach, nor is it sensitivity-enhancing or suited for very large data sets.
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