Ensemble Approach for Recovering Phase Synchronization from Time Series

An ensemble approach is presented for the reconstruction of a phase synchronization diagram from time series. As an example system, we analyze a forced Colpitts oscillator to show that synchronization diagram reconstructed by a single nonlinear model depends sensitively upon the model parameters, which should be estimated with a considerable amount of care. This dependence can be crucial for a precise recovery of the synchronization phenomena. To overcome this weakness, an ensemble approach is introduced. Two types of techniques, namely, (I) ensemble regression and (II) ensemble classification, are developed to show that they provide much more robust and reliable reconstruction of the synchronization diagram compared to the conventional single modeling approach.