Abstract
2DCOS analysis of dynamic spectra, which can be approximated in the form of a polynomial function by the least squares curve fitting method, is carried out. Curve fitting provides a practical way of condensing a large spectral dataset in terms of a small number of fitting parameters and filtering out noise and superfluous spectral intensity variations from the raw spectra. Pertinent features of the findings are illustrated by using a simple simulated spectral data subjected to curve fitting with polynomials. Closed-form analytical expressions for 2D correlation spectra are obtained from the polynomial functions used for the curve fitting and their Hilbert transform counterpart. Such analytical expressions provide useful insight into the inner working of 2DCOS analysis, especially the role of slope and curvature of spectral intensity variations, in determining the signs of cross peaks used in the interpretation of 2D spectra.
Sign-in/Register to access full text options 
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.
