Add to ORKGSummary. We describe dependencies in bivariate time series by appearance of equal or similar recurrence patterns. Various recurrence concepts and parameters are discussed. They are applied to detect synchronization in model systems of coupled oscillators and coupling in EEG data. Key words: time series analysis, nonlinear dynamics, recurrence, synchronization
Synchronization behavior of electroencephalographic (EEG) signals is important for decoding informat...
Couplings in complex real-world systems are often nonlinear and scale dependent. In many cases, it i...
In the last decade, the applications of the recurrence plot analy-sis method make it a valuable alte...
First synchronization phenomena in coupled complex systems are presented. Then it is explained how t...
International audienceWe introduce a method to visualize dependencies between two time series by app...
International audienceTransients in non-linear biological signals (e.g., population dynamics or phys...
This book features 13 papers presented at the Fifth International Symposium on Recurrence Plots, hel...
In the light of the results obtained during the last two decades in analysis of signals by time ...
Recurrence Plots (RPs) were developed at the end of the 1980’s as visualization tools forcomplex dyn...
Different cases of generalized synchronization are discussed with emphasis on methods for detecting ...
Multivariate time series analysis is extensively used in neurophysiology with the aim of studying th...
We introduce a geometric method for identifying the coupling direction between two dynamical systems...
The recurrence times between extreme events have been the central point of statistical analyses in m...
Complex systems are characterized by deterministic laws (which often may be hidden) and randomness. ...
In recurrence analysis, the τ-recurrence rate encodes the periods of the cycles of the underlying hi...
Synchronization behavior of electroencephalographic (EEG) signals is important for decoding informat...
Couplings in complex real-world systems are often nonlinear and scale dependent. In many cases, it i...
In the last decade, the applications of the recurrence plot analy-sis method make it a valuable alte...
First synchronization phenomena in coupled complex systems are presented. Then it is explained how t...
International audienceWe introduce a method to visualize dependencies between two time series by app...
International audienceTransients in non-linear biological signals (e.g., population dynamics or phys...
This book features 13 papers presented at the Fifth International Symposium on Recurrence Plots, hel...
In the light of the results obtained during the last two decades in analysis of signals by time ...
Recurrence Plots (RPs) were developed at the end of the 1980’s as visualization tools forcomplex dyn...
Different cases of generalized synchronization are discussed with emphasis on methods for detecting ...
Multivariate time series analysis is extensively used in neurophysiology with the aim of studying th...
We introduce a geometric method for identifying the coupling direction between two dynamical systems...
The recurrence times between extreme events have been the central point of statistical analyses in m...
Complex systems are characterized by deterministic laws (which often may be hidden) and randomness. ...
In recurrence analysis, the τ-recurrence rate encodes the periods of the cycles of the underlying hi...
Synchronization behavior of electroencephalographic (EEG) signals is important for decoding informat...
Couplings in complex real-world systems are often nonlinear and scale dependent. In many cases, it i...
In the last decade, the applications of the recurrence plot analy-sis method make it a valuable alte...