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      Multivariate weighted complex network analysis for characterizing nonlinear dynamic behavior in two-phase flow

      , , ,
      Experimental Thermal and Fluid Science
      Elsevier BV

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          Scale-free networks: a decade and beyond.

          For decades, we tacitly assumed that the components of such complex systems as the cell, the society, or the Internet are randomly wired together. In the past decade, an avalanche of research has shown that many real networks, independent of their age, function, and scope, converge to similar architectures, a universality that allowed researchers from different disciplines to embrace network theory as a common paradigm. The decade-old discovery of scale-free networks was one of those events that had helped catalyze the emergence of network science, a new research field with its distinct set of challenges and accomplishments.
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            Networks formed from interdependent networks

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              Complex Network from Pseudoperiodic Time Series: Topology versus Dynamics

              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 these networks for various time series and find that time series with different dynamics exhibit distinct topological structures. Specifically, noisy periodic signals correspond to random networks, and chaotic time series generate networks that exhibit small world and scale free features. We show that this distinction in topological structure results from the hierarchy of unstable periodic orbits embedded in the chaotic attractor. Standard measures of structure in complex networks can therefore be applied to distinguish different dynamic regimes in time series. Application to human electrocardiograms shows that such statistical properties are able to differentiate between the sinus rhythm cardiograms of healthy volunteers and those of coronary care patients.
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                Author and article information

                Journal
                Experimental Thermal and Fluid Science
                Experimental Thermal and Fluid Science
                Elsevier BV
                08941777
                January 2015
                January 2015
                : 60
                :
                : 157-164
                Article
                10.1016/j.expthermflusci.2014.09.008
                9657cf16-b8f7-4210-8d55-d86ef32ad0ad
                © 2015
                History

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