Two-dimensional correlation analysis

被引：71

作者：

Harrington, PD ^{[1
]}

Urbas, A ^{[1
]}

Tandler, PJ ^{[1
]}

机构：

[1] Ohio Univ, Clippinger Labs, Dept Chem & Biochem, Ctr Intelligent Chem Instrumentat, Athens, OH 45701 USA

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 2000年 / 50卷 / 02期

关键词：

2D correlation analysis; multivariate data; cross-correlation;

D O I：

10.1016/S0169-7439(99)00062-3

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This tutorial reviews the recent computational advances in two-dimensional (2D) correlation spectroscopy, presents the theory, and provides examples applying 2D correlation analysis. Two-dimensional correlation analysis is a method for visualizing the relationships among the variables in multivariate data and their temporal behavior by applying the complex cross-correlation function. This function measures correlations that occur at the same rate or frequency with respect to the data acquisition time. The complex cross-correlation function yields real and imaginary components that contain information about the phase behavior of the variables. The real component provides information about mutually dependent in-phase variations. Variations that occur out-of-phase (with time lags or leads) are given by the imaginary component. Two-dimensional correlation analysis is a general analysis method that can be used for the treatment of data from a variety of applications including image, distribution, environmental, and kinetic analysis. (C) 2000 Elsevier Science B.V. All rights reserved.

引用

页码：149 / 174

页数：26

共 20 条

[1] Simplified and efficient method of computing generalized two-dimensional correlation spectra [J].