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The degree centrality and clustering coefficient of nodes in the recurrence network of a time series reveal complementary geometrical properties of the dynamics in phase space. This helps to distinguish between the various dynamical regimes of a complex nonlinear system. The logistic map provides a good model for dynamical transitions among regular, laminar, and chaotic behavior of a dynamical system. The evolution and properties of the time series depend on the control parameter ... . Observe how the degree and clustering series and frequency distribution evolve as you change the control parameter ... . Can you identify periodic windows in a sea of chaos? As you increase the recurrence threshold ... , the recurrence network measures slowly approach those expected for a fully connected network.

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      EUN,LOM,LRE4,work-cmr-id:397401,http://demonstrations.wolfram.com:http://demonstrations.wolfram.com/RecurrenceNetworkMeasuresForTheLogisticMap/,ilox,learning resource exchange,LRE metadata application profile,LRE

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