Literature DB >> 28387135

Analytical and Numerical Characterization of Autocorrelation and Perturbation-Correlation Moving-Window Methods.

Young Jong Lee1.   

Abstract

Moving-window (MW) approaches to two-dimensional correlation spectroscopy (2D-COS) make it possible to characterize spectral changes occurring in a narrow range of perturbation variable (e.g., time, temperature, and concentration). Despite the wide range of application, the physical meanings of MW correlation intensities have been only qualitatively associated with the direction and curvature of spectral intensity change with regard to a perturbation variable. Here are full and simplified analytical expressions of autocorrelation moving-window (ACMW) and synchronous and asynchronous perturbation-correlation moving-window ( s-PCMW and as-PCMW) intensities. When the window is set sufficiently narrower than the bandwidth of spectral change, the square root of ACMW intensity and s-PCMW intensity becomes proportional to the first order derivative, and as-PCMW intensity becomes proportional to the negative of the second order derivative. This paper demonstrates that both ACMW and PCMW profiles can be significantly altered by non-uniform perturbation spacing. It is also found that intensity noise can cause ACMW to display a false offset drift. This analytical and numerical characterization of the two MW correlation intensities elucidates their physical meanings and ascertains the analysis conditions for reliable interpretation.

Keywords:  ACMW; PCMW; Two-dimensional correlation spectroscopy (2D-COS); autocorrelation moving-window; perturbation-correlation moving-window; phase transition

Year:  2017        PMID: 28387135     DOI: 10.1177/0003702816681169

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  1 in total

1.  Least Squares Moving-Window Spectral Analysis.

Authors:  Young Jong Lee
Journal:  Appl Spectrosc       Date:  2017-01-20       Impact factor: 2.388

  1 in total

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