Projects per year
Abstract
Entropy metrics (for example, permutation entropy) are nonlinear measures of irregularity in time series (one-dimensional data). Some of these entropy metrics can be generalised to data on periodic structures such as a grid or lattice pattern (two-dimensional 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 well-established 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 |
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Pages (from-to) | 288-300 |
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 | E-pub ahead of print - 13 Apr 2022 |
Keywords / Materials (for Non-textual outputs)
- 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 Finished
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Nonlinear analysis and modelling of multivariate signals on networks
1/11/20 → 31/10/23
Project: Research
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Permutation Entropy for Graph Signals: Theoretical framework and application to neuroimaging data
Javier Escudero (Invited speaker)
6 Mar 2024Activity: Academic talk or presentation types › Invited talk
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From multivariate time series to graphs data and beyond: Extending entropy analysis techniques to irregularly sampled data
Javier Escudero Rodriguez (Invited speaker)
9 Mar 2023Activity: Academic talk or presentation types › Invited talk
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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
File