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Abstract
Entropy metrics (for example, permutation entropy) are nonlinear measures of irregularity in time series (onedimensional data). Some of these entropy metrics can be generalised to data on periodic structures such as a grid or lattice pattern (twodimensional data) using its symmetry, thus enabling their application to images. However, these metrics have not been developed for signals sampled on irregular domains, defined by a graph. Here, we define for the first time an entropy metric to analyse signals measured over irregular graphs by generalising permutation entropy, a wellestablished nonlinear metric based on the comparison of neighbouring values within patterns in a time series. Our algorithm is based on comparing signal values on neighbouring nodes, using the adjacency matrix. We show that this generalisation preserves the properties of classical permutation for time series and the recent permutation entropy for images, and it can be applied to any graph structure with synthetic and real signals. We expect the present work to enable the extension of other nonlinear dynamic approaches to graph signals.
Original language  English 

Pages (fromto)  288300 
Number of pages  13 
Journal  IEEE Transactions on Signal and Information Processing Over Networks 
Volume  8 
Early online date  13 Apr 2022 
DOIs  
Publication status  Epub ahead of print  13 Apr 2022 
Keywords
 Graph signal processing
 graph Laplacian
 permutation entropy
 adjacency matrix
 IRREGULARITY
 Nonlinearity dynamics
 Topology
 Entropy metric
 Irregularity
 Adjacency matrix
 Nonlinearity Dynamics
 Graph Laplacian
 Permutation entropy
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Dive into the research topics of 'Permutation Entropy for Graph Signals'. Together they form a unique fingerprint.Projects
 1 Active

Nonlinear analysis and modelling of multivariate signals on networks
1/11/20 → 31/10/23
Project: Research
Activities
 1 Oral presentation

Entropy metrics for graph signals
John Stewart Fabila Carrasco (Speaker), Javier Escudero Rodriguez (Supervisor) & Chao Tan (Supervisor)
30 Nov 2022Activity: Academic talk or presentation types › Oral presentation
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