A new network entropy measure, the average binary entropy of normalized node degrees, is shown to characterize chaotic attractors and quantify structural information loss through link density changes.
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Quantifying information loss on chaotic attractors through recurrence networks
A new network entropy measure, the average binary entropy of normalized node degrees, is shown to characterize chaotic attractors and quantify structural information loss through link density changes.