Symmetrization effects of k-nearest neighbor recurrence plots on network motif organizations in time series of nonlinear dynamical systems

抄録

Some studies started analyzing time series via complex networks in the noughties. A study reported that time series, which were transformed into networks via recurrence plots (RPs), especially k-nearest neighbor RP, exhibited superfamily phenomena resulting from the network motif analysis. However, it is not hard to imagine that the transformation properties drastically change the results of the motif analysis. In this study, we examine that by introducing another type of RP.As a result, the RP employed in this study works better for the superfamily phenomena among the time series than the previously used RP.