This paper presents a new approach for analysing the structural properties of time series
from complex systems. Starting from the concept of recurrences in phase space, the …

Recently, different approaches have been proposed for studying basic properties of time
series from a complex network perspective. In this work, the corresponding potentials and …

Complex networks are an important paradigm of modern complex systems sciences which
allows quantitatively assessing the structural properties of systems composed of different …

In the last decade, there has been a growing body of literature addressing the utilization of
complex network methods for the characterization of dynamical systems based on time …

Recently, several complex network approaches to time series analysis have been
developed and applied to study a wide range of model systems as well as real-world data …

We propose a novel approach for analysing time series using complex network theory. We
identify the recurrence matrix (calculated from time series) with the adjacency matrix of a …

Recurrence networks are a powerful nonlinear tool for time series analysis of complex
dynamical systems. While there are already many successful applications ranging from …

Recently a new framework has been proposed to explore the dynamics of pseudoperiodic
time series by constructing a complex network [J. Zhang, M. Small, Phys. Rev. Lett. 96 …

Revealing complicated behaviors from time series constitutes a fundamental problem of
continuing interest and it has attracted a great deal of attention from a wide variety of fields …

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis
toolbox) open source software package for applying and combining modern methods of data …