New types of nonlinear auto-correlations of bivariate data and their applications

New types of nonlinear auto-correlations of bivariate data and their applications

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Article ID: iaor20123646
Volume: 218
Issue: 17
Start Page Number: 8951
End Page Number: 8967
Publication Date: May 2012
Journal: Applied Mathematics and Computation
Authors: , ,
Keywords: computers: information, sets, statistics: multivariate
Abstract:

The paper introduces new types of nonlinear correlations between bivariate data sets and derives nonlinear auto‐correlations on the same data set. These auto‐correlations are of different types to match signals with different types of nonlinearities. Examples are cited in all cases to make the definitions meaningful. Next correlogram diagrams are drawn separately in all cases; from these diagrams proper time lags/delays are determined. These give rise to independent coordinates of the attractors. Finally three dimensional attractors are reconstructed in each case separately with the help of these independent coordinates. Moreover for the purpose of making proper distinction between the signals, the attractors so reconstructed are quantified by a new technique called ‘ellipsoid fit’.

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