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 …

The availability of time series of the evolution of the properties of physical systems is
increasing, stimulating the development of many novel methods for the extraction of …

We present an assessment of the practical value of existing traditional and non-standard
measures for discriminating healthy people from people with Parkinson? s disease (PD) by …

We construct complex networks from pseudoperiodic time series, with each cycle
represented by a single node in the network. We investigate the statistical properties of …

Complex networks are an important paradigm of modern complex systems sciences which
allows quantitatively assessing the structural properties of systems composed of different …

In this paper, different types of classification methods are compared for effective diagnosis of
Parkinson's diseases. The reliable diagnosis of Parkinson's disease is notoriously difficult to …

Studying the interaction between a system's components and the temporal evolution of the
system are two common ways to uncover and characterize its internal workings. Recently …

There is nowadays a constant flux of data being generated and collected in all types of real
world systems. These data sets are often indexed by time, space, or both requiring …

Recently a new framework has been proposed to explore the dynamics of pseudoperiodic
time series by constructing a complex network [J. Zhang, M. Small, Phys. Rev. Lett. 96 …

We present the modification of natural visibility graph (NVG) algorithm used for the map**
of the time series to the complex networks (graphs). We propose the parametric natural …