An On-Line Class-Specific GC/FTIR Reconstruction from Interferometric Data

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Abstract
GC/FTIR data have bean used to construct functional group-specific chromatograms. The classification of the GC peaks is based on the interferometric data. Because no Fourier transforms are involved, the algorithm is computationally fast enough to be performed on-line during data collection. The Gram-Schmidt reconstruction was used to locate the eluting compounds in the GC data, and pattern recognition techniques were used to classify the compounds. A linear learning machine and composite segment were compared, and the composite segment reconstruction was found to be superior.

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