Abstract
Based on the geometrical look on the mathematical structure of a set of noisy spectra composed of two factors, some general properties of any set of noisy spectra are derived and discussed. It is then pointed out that the ability to detect the presence of lower contributing factor depends on the choice of the criterion applied together with principal component analysis (PCA). The efficiency of two particular criteria were compared by the application to sets of simulated spectra of known composition. The comparison showed that the detection limit can be improved by a factor of 2 or 3 by a proper choice of the criterion. Removing the less informative parts of the spectra results in an additional improvement of the detection limit.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
