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.
Physical Review Letters 50(5), 346–349 (1983)
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Sample entropy is extended to graph signals via topology-aware multi-hop embeddings to quantify nonlinear dynamics on networks.
Brody exponent β is calibrated for 2D spatial point processes with a corrected CSR baseline of 0.96±0.15 and validated β–r_excl correlation of ρ=0.988, supported by controls on primes and manufactured surfaces.
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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.