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.
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