In the last decade, there has been a growing body of literature addressing the utilization of
complex network methods for the characterization of dynamical systems based on time …

Revealing complicated behaviors from time series constitutes a fundamental problem of
continuing interest and it has attracted a great deal of attention from a wide variety of fields …

Introduction In recent times, an upsurge in the investigation related to the effects of
meditation in reconditioning various cardiovascular and psychological disorders is seen. In …

The family of image visibility graphs (IVG/IHVGs) have been recently introduced as simple
algorithms by which scalar fields can be mapped into graphs. Here we explore the …

The Poincaré plot is a geometrical technique used to visualize and quantify the correlation
between two consecutive data points in a time-series. Since the dynamics of fluctuations in …

Empirical tight-binding (ETB) methods are widely used in atomistic device simulations.
Traditional ways of generating the ETB parameters rely on direct fitting to bulk experiments …

The cardiac dynamics during meditation is explored quantitatively with two chaos-based non-
linear techniques viz. multi-fractal detrended fluctuation analysis and visibility network …

Visibility algorithms transform time series into graphs and encode dynamical information in
their topology, paving the way for graph-theoretical time series analysis as well as building a …

Analysis of heart rate variability (HRV) can be applied to assess the autonomic nervous
system (ANS) sympathetic and parasympathetic activity. Since living systems are non-linear …

We report on a large-scale characterization of river discharges by employing the network
framework of the horizontal visibility graph. By mapping daily time series from 141 different …