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|Title:||Development of 2D- and 3D-BTEM for pattern recognition in higher-order spectroscopic and other data arrays||Authors:||GUO LIANGFENG||Keywords:||higher-order spectroscopic data analysis, entropy minimization, 2D-NMR, 2D fluorescence spectra, spectral deconvolution, inverse problem||Issue Date:||30-May-2006||Citation:||GUO LIANGFENG (2006-05-30). Development of 2D- and 3D-BTEM for pattern recognition in higher-order spectroscopic and other data arrays. ScholarBank@NUS Repository.||Abstract:||In the past ten years, considerable efforts have been invested in developing a new and general approach to chemical reaction system identification. Normally such system identification is built on the numerical analysis of in-situ spectroscopic measurements of reactive systems using some advanced signal processing / chemometrics procedures. Currently, the analysis of 100-1000 MB of 1D FTIR spectral data analysis is a rather routine procedure. However, with many other spectroscopies i.e. XRD, NMR, as well as simultaneous multiple spectroscopies, the amount and complexity of the data sets increases enormously. In addition, new types of data structures i.e. 2D and 3D data set, originating from some very advanced instrumentation leads to higher order data sets. Therefore, the need to develop methods to identify patterns in these 3 and 4 arrays (tensors) is imperative. Moreover, these methods must be computationally efficient, in order to deal with such an increase in data. The goal of the PhD research was to investigate large scale inverse chemometrics problems, in particular 2D NMR, 2D fluorescence spectral data sets, images, etc.||URI:||http://scholarbank.nus.edu.sg/handle/10635/15449|
|Appears in Collections:||Ph.D Theses (Open)|
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