This paper describes two mathematical approaches applied for decoding the complex signal of GC separations of multicomponent mixtures. The methods are helpful in extracting analytical information since separation of all the components present in the sample is still far from being achieved. One methos is based on the Statistical Degree of Peak Overlapping, the other studies the autocovariance function computed on the experimental digitized GC signal.
Decoding complex multicomponent chromatograms
PIETROGRANDE, Maria Chiara
2001
Abstract
This paper describes two mathematical approaches applied for decoding the complex signal of GC separations of multicomponent mixtures. The methods are helpful in extracting analytical information since separation of all the components present in the sample is still far from being achieved. One methos is based on the Statistical Degree of Peak Overlapping, the other studies the autocovariance function computed on the experimental digitized GC signal.File in questo prodotto:
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