Recurrence-plot-based recurrence networks are an approach used to analyze time series using a complex networks theory. In both approaches – recurrence plots and recurrence networks –, a threshold to identify recurrent states is required. The selection of the threshold is important in order to avoid bias of the recurrence network results. In this paper, we propose a novel method to choose a recurrence threshold adaptively. We show a comparison between the constant threshold and adaptive threshold cases to study period–chaos and even period–period transitions in the dynamics of a prototypical model system. This novel method is then used to identify climate transitions from a lake sediment record.
Eroglu, D., Marwan, N., Prasad, S., & Kurths, J. (2014). Finding recurrence networks’ threshold adaptively for a specific time series. Nonlinear Processes in Geophysics, 21(6), 1085-1092. https://doi.org/10.5194/npg-21-1085-2014