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Table 2 Significance of patterns in recurrence plots (after Marwan et al. 2007a)

From: Nonlinear dynamical analysis of GNSS data: quantification, precursors and synchronisation

Pattern Significance
Homogeneous The process is stationary
Fading pattern to upper right or lower left Non-stationary data; the process contains a trend or drift
Disruptions (horizontal or vertical) Non-stationary data; some states are far from the normal; transitions may have occurred
Periodic or quasi-periodic patterns The process is cyclic. The vertical (or horizontal) distance between periodic lines corresponds to the period. Variations in the distance mean quasi-periodicity in the process.
Single isolated points Strong fluctuations in the process. The process may be uncorrelated or anti-correlated.
Diagonal lines (parallel to the LOI) The evolution of the system is similar over the length of the line. If lines appear next to single isolated points the process may be chaotic.
Diagonal lines (orthogonal to the LOI) The evolution of states at different times is similar but with reverse timing.
Vertical and horizontal lines or clusters States do not change with time or change slowly
Lines not parallel to the LOI-sometimes curved. The evolution of states is similar at different times but the rate of evolution changes with time. The dynamics of the system is changing with time.