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Use of global symmetries in automated signal class recognition by a bayesian method

Schulte, A. C. ; Görler, A. ; Antz, C. ; Neidig, Klaus-Peter ; Kalbitzer, Hans Robert



Abstract

Automated or semiautomated pattern recognition in multidimensional NMR spectroscopy is strongly hampered by the large number of noise and artifact peaks occurring under practical conditions. A general Bayesian method which is able to assign probabilities that observed peaks are members of given signal classes (e.g., the class of true resonance peaks or the class of noise and artifact peaks) was ...

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