Recurrence plot and recurrence quantification analysis

Toolbox of recurrence plot and recurrence quantification analysis

% This toolbox shows the examples to use the tool box of recurrence plot and

% recurrence quantification analysis

Functions include:

(1) %Estimates the time delayed mutual information of the data set

(2) %Determines the fraction of false nearest neighbors.

(3) produce a recurrence plot of the, possibly multivariate,

%data set. That means, for each point in the data set it looks for all

%points, such that the distance between these two points is smaller

%than a given size in a given embedding space.

(4) produce a threshold recurrence plot of the, possibly multivariate,

%data set. That means, for each point in the data set it looks for all

%points, such that the distance between these two points is smaller

%than a given size in a given embedding space.

(5) calculate the RQA statistics for a recurrence plot.

% If you find this toolbox useful, please cite the following paper:

[1] Yang, Hui. “Multiscale Recurrence Quantification Analysis of Spatial Cardiac Vectorcardiogram Signals.” IEEE Transactions on Biomedical Engineering, vol. 58, no. 2, Institute of Electrical and Electronics Engineers (IEEE), Feb. 2011, pp. 339–47, doi:10.1109/tbme.2010.2063704.

[2] Chen, Yun, and Hui Yang. “Multiscale Recurrence Analysis of Long-Term Nonlinear and Nonstationary Time Series.” Chaos, Solitons Fractals, vol. 45, no. 7, Elsevier BV, July 2012, pp. 978–87, doi:10.1016/j.chaos.2012.03.013.

[3] Yang, Hui. “Mining Nonlinear Dynamics in Operational Data for Process Improvement.” Tutorials in Operations Research: Advancing the Frontiers of OR/MS: From Methodologies to Applications, INFORMS, 2023, pp. 109–32, doi:10.1287/educ.2023.0261.