Using the visibility graph algorithm, a complex network can be associated with a time series, such that the properties of the time series can be obtained by studying those of the network. Any time series value becomes a network node, and the number of other nodes it is connected to can be quantified. The degree of connectivity of a node is positively correlated with its magnitude, and the graph inherits some non-linear properties of the time series.
In this session, Eric will present a use case of this method to compare tachograms from chronic heart disease patients and healthy subjects.
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