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 …

Detecting drowsiness in drivers, especially multi-level drowsiness, is a difficult problem that
is often approached using neurophysiological signals as the basis for building a reliable …

Many complex and interesting phenomena in nature are due to nonlinear phenomena. The
theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a …

This review covers the group of data-analysis techniques collectively referred to as
symbolization or symbolic time-series analysis. Symbolization involves transformation of raw …

This study examines the effect of the 2008 global financial crisis on the crude oil market. We
use the Hurst exponent, Shannon entropy, and the scaling exponent to characterize the …

We propose a method to measure real-valued time series irreversibility which combines two
different tools: the horizontal visibility algorithm and the Kullback-Leibler divergence. This …

Time irreversibility, a fundamental property of nonequilibrium systems, should be of
importance in assessing the status of physiological processes that operate over a wide …

The assessment of time irreversibility, ie, of the lack of invariance of the statistical properties
of a system under the operation of time reversal, is a topic steadily gaining attention within …

The absence of time-reversal symmetry is a fundamental property of many nonlinear time
series. Here, we propose a new set of statistical tests for time series irreversibility based on …

This study investigates the effects of stock market uncertainty on economic fundamentals,
represented by economic activities and systemic risk, in China. To capture the uncertainty in …