Delay embedding methods are a staple tool in the field of time series analysis and
prediction. However, the selection of embedding parameters can have a big impact on the …

The last decade has witnessed a number of important and exciting developments that had
been achieved for improving recurrence plot-based data analysis and to widen its …

Abstract Soil moisture‐Precipitation (SM‐P) coupling, especially the causality from SM to P
(SM→ P), is an important and highly debated topic. The causal inference from observational …

We present a fully automated method for the optimal state space reconstruction from
univariate and multivariate time series. The proposed methodology generalizes the time …

Infectious diseases are notorious for their complex dynamics, which make it difficult to fit
models to test hypotheses. Methods based on state-space reconstruction have been …

Abstract The Belousov–Zhabotinsky chemical reaction is famous for its oscillatory behavior
occurring due to inherent physicochemical processes. Oscillations of the Belousov …

Chaotic time series are widely present in practice, but due to their characteristics—such as
internal randomness, nonlinearity, and long-term unpredictability—it is difficult to achieve …

A novel idea for an optimal time delay state space reconstruction from uni-and multivariate
time series is presented. The entire embedding process is considered as a game, in which …

Delay-coordinate map** is an effective and widely used technique for reconstructing and
analyzing the dynamics of a nonlinear system based on time-series outputs. The efficacy of …

A paradigm for optimal state-space reconstruction with nonuniform time delays is proposed.
A comparison based on a diffeomorphic measure and a smoothness cost function shows …