Topic
Recurrence quantification analysis
About: Recurrence quantification analysis is a research topic. Over the lifetime, 752 publications have been published within this topic receiving 25911 citations.
Papers published on a yearly basis
Papers
TL;DR: The method introduces complexity parameters for time series based on comparison of neighboring values and shows that its complexity behaves similar to Lyapunov exponents, and is particularly useful in the presence of dynamical or observational noise.
Abstract: We introduce complexity parameters for time series based on comparison of neighboring values. The definition directly applies to arbitrary real-world data. For some well-known chaotic dynamical systems it is shown that our complexity behaves similar to Lyapunov exponents, and is particularly useful in the presence of dynamical or observational noise. The advantages of our method are its simplicity, extremely fast calculation, robustness, and invariance with respect to nonlinear monotonous transformations.
4,537 citations
TL;DR: The aim of this work is to provide the readers with the know how for the application of recurrence plot based methods in their own field of research, and detail the analysis of data and indicate possible difficulties and pitfalls.
3,624 citations
TL;DR: In this article, a graphical tool for measuring the time constancy of dynamical systems is presented and illustrated with typical examples, and the tool can be used to measure the time complexity of a dynamical system.
Abstract: A new graphical tool for measuring the time constancy of dynamical systems is presented and illustrated with typical examples.
3,281 citations
TL;DR: This paper illustrates how recurrence plots can take single physiological measurements, project them into multidimensional space by embedding procedures, and identify time correlations (recurrences) that are not apparent in the one-dimensional time series.
Abstract: Physiological systems are best characterized as complex dynamical processes that are continuously subjected to and updated by nonlinear feedforward and feedback inputs. System outputs usually exhibit wide varieties of behaviors due to dynamical interactions between system components, external noise perturbations, and physiological state changes. Complicated interactions occur at a variety of hierarchial levels and involve a number of interacting variables, many of which are unavailable for experimental measurement. In this paper we illustrate how recurrence plots can take single physiological measurements, project them into multidimensional space by embedding procedures, and identify time correlations (recurrences) that are not apparent in the one-dimensional time series. We extend the original description of recurrence plots by computing an array of specific recurrence variables that quantify the deterministic structure and complexity of the plot. We then demonstrate how physiological states can be assessed by making repeated recurrence plot calculations within a window sliding down any physiological dynamic. Unlike other predominant time series techniques, recurrence plot analyses are not limited by data stationarity and size constraints. Pertinent physiological examples from respiratory and skeletal motor systems illustrate the utility of recurrence plots in the diagnosis of nonlinear systems. The methodology is fully applicable to any rhythmical system, whether it be mechanical, electrical, neural, hormonal, chemical, or even spacial.
1,473 citations
TL;DR: Recurrence plots have been advocated as a useful diagnostic tool for the assessment of dynamical time series by quantifying certain features of these plots which may be helpful in determining embeddings and delays.
1,155 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 14 |
| 2024 | 17 |
| 2023 | 49 |
| 2022 | 97 |
| 2021 | 36 |
| 2020 | 42 |