Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12794
Title: Recurrence-based time series analysis by means of complex network methods
Authors: Donner, RV
Small, M
Donges, JF
Marwan, N
Zou, Y
Xiang, R
Kurths, J
Keywords: Complex networks
recurrence plots
time series analysis
Issue Date: 2011
Publisher: World Scientific
Source: International journal of bifurcation and chaos in applied sciences and engineering, 2011, v. 21, no. 4, p. 1019-1046 How to cite?
Journal: International journal of bifurcation and chaos in applied sciences and engineering 
Abstract: Complex networks are an important paradigm of modern complex systems sciences which allows quantitatively assessing the structural properties of systems composed of different interacting entities. During the last years, intensive efforts have been spent on applying network-based concepts also for the analysis of dynamically relevant higher-order statistical properties of time series. Notably, many corresponding approaches are closely related to the concept of recurrence in phase space. In this paper, we review recent methodological advances in time series analysis based on complex networks, with a special emphasis on methods founded on recurrence plots. The potentials and limitations of the individual methods are discussed and illustrated for paradigmatic examples of dynamical systems as well as for real-world time series. Complex network measures are shown to provide information about structural features of dynamical systems that are complementary to those characterized by other methods of time series analysis and, hence, substantially enrich the knowledge gathered from other existing (linear as well as nonlinear) approaches.
URI: http://hdl.handle.net/10397/12794
ISSN: 0218-1274
EISSN: 1793-6551
DOI: 10.1142/S0218127411029021
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