SampEn_G generalizes sample entropy to graph signals via multi-hop graph embeddings based on the graph shift operator, reducing to the classical version on path graphs and showing sensitivity to nonlinear dynamics.
IEEE Signal Processing Letters 23(5), 610–614 (2016)
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Sample entropy is extended to graph signals via topology-aware multi-hop embeddings to quantify nonlinear dynamics on networks.
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Sample entropy for graph signals: An approach to nonlinear analysis of graph signals
SampEn_G generalizes sample entropy to graph signals via multi-hop graph embeddings based on the graph shift operator, reducing to the classical version on path graphs and showing sensitivity to nonlinear dynamics.
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Sample entropy for graph signals: An approach to nonlinear dynamic analysis of data on networks
Sample entropy is extended to graph signals via topology-aware multi-hop embeddings to quantify nonlinear dynamics on networks.