Related Experiment Video
Updated: Aug 15, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Recurrence plot analysis of nonstationary data: the understanding of curved patterns
A Facchini1, H Kantz, E Tiezzi
1Dept. of Chemical and Biosystems Sciences, Siena University, Siena, Italy. a.facchini@unisi.it
Abstract:
Recurrence plots of the calls of the Nomascus concolor (Western black crested gibbon) and Hylobates lar (White-handed gibbon) show characteristic circular, curved, and hyperbolic patterns superimposed to the main temporal scale of the signal. It is shown that these patterns are related to particular nonstationarities in the signal. Some of them can be reproduced by artificial signals like frequency modulated sinusoids and sinusoids with time divergent frequency. These modulations are too faint to be resolved by conventional time-frequency analysis with similar precision. Therefore, recurrence plots act as a magnifying glass for the detection of multiple temporal scales in slightly modulated signals. The detected phenomena in these acoustic signals can be explained in the biomechanical context by taking in account the role of the muscles controlling the vocal folds.
Related Concept Videos
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Residual Plots
When the residual values are plotted against the variable x, it is called a residual...
Scatter Plot
Curvature and Its Interpretation
Polar Curves
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...

