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UNDERDETERMINED BLIND EXTRACTION OF COMPONENTS FROM MIXTURES IN 1D AND 2D NMR SPECTROSCOPY AND MASS SPECTROMETRY BY MEANS OF COMBINED SPARSE COMPONENT ANALYSIS AND DETECTION OF SINGLE COMPONENT POINTS
UNDERDETERMINED BLIND EXTRACTION OF COMPONENTS FROM MIXTURES IN 1D AND 2D NMR SPECTROSCOPY AND MASS SPECTROMETRY BY MEANS OF COMBINED SPARSE COMPONENT ANALYSIS AND DETECTION OF SINGLE COMPONENT POINTS
The present invention relates to the blind extraction of pure components from mixtures recorded in the fields of ID or 2D NMR spectroscopy and mass spectrometry. Specifically, the invention is related to the application of sparse component analysis in combination with detection of single component points to blind decomposition of NMR spectroscopy or mass spectrometry data X into pure components S and concentration matrix A, when the number of pure components S is greater than the number of mixtures X. NMR mixtures are transformed into wavelet domain, since pure components int the wavelet domain are sparser than in the recording domain. By means of a direction based criterion single component points (SCPs) of the mixtures in the wavelet domain are detected where only one pure component is active. These SCPs are used for the estimation of the unknown number of pure components and for the estimation of the concentration matrix by means of data clustering methods. The pure components are estimated in frequency domain, e.g. by means of linear programming. Mass spectrometry mixture signals are extended by analytical continuation which is necessary to obtain a complex signal as is required by direction based SCPs detection criterion. The estimated pure components are ranked using a negentropy-based criterion.
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