Effect of the window size in moving-window two-dimensional correlation analysis

Abstract

The effect of window size in the moving-window two-dimensional (MW2D) correlation analysis is studied. In the specific case of sigmoidal signal variation, the results of MW2D correlation with various window sizes have indicated that too large a window is not effective to obtain the information along the perturbation direction, because the window always includes excessive perturbation region more than needed. It just offers too much information broadly distributed along the perturbation direction. On the other hand, too small a window is not effective either, because an excessively small window is subject to exhibit an undesirable effect of the high noise level in the data. Thus, we have investigated index to determine the optimal window size in the MW2D correlation analysis. Autocorrelation spectra of a simulated spectral data were obtained with all possible window size. Peak height of each autocorrelation peak was plotted as a function of the window size, and it was revealed that this parameter can be used as a convenient index for determining the optimal window size in the specific case studied. This index was applied to temperature-dependent IR spectra of a poly(methyl methacrylate) (PMMA) film to optimize the window wise in MW2D analysis. The result showed that the index can effectively optimize the window size in the MW2D analysis of the IR spectra of PMMA.