Projects per year
Abstract
Entropy metrics are nonlinear measures to quantify the complexity of time series. Among them, permutation entropy is a commonly used metric due to its robustness and fast computation. Multivariate entropy metrics techniques are needed to analyse data consisting of more than one time series. To this end, we present a multivariate permutation entropy, MPEG, using a graphbased approach. Given a multivariate signal, the algorithm to compute MPEG involves two main steps: 1) we construct an underlying graph G as the Cartesian product of two graphs G1 and G2, where G1 preserves temporal information of each times series and G2 models the relations between different channels; and 2) we consider the multivariate signal as samples defined on the regular graph G and apply the recently introduced permutation entropy for graphs. Our graphbased approach gives the flexibility to consider diverse types of cross channel relationships and signals, and it overcomes with the limitations of current multivariate permutation entropy.
Original language  English 

Title of host publication  2022 30th European Signal Processing Conference (EUSIPCO) 
Publisher  European Signal Processing Conference, EUSIPCO 
Number of pages  5 
ISBN (Electronic)  9789082797091, 9789082797084 
ISBN (Print)  9781665467995 
Publication status  Epub ahead of print  18 Oct 2022 
Event  30th European Signal Processing Conference  Belgrade , Serbia Duration: 29 Aug 2022 → 2 Sep 2022 https://2022.eusipco.org/ 
Publication series
Name  European Signal Processing Conference (EUSIPCO) 

Publisher  IEEE 
ISSN (Print)  22195491 
ISSN (Electronic)  20761465 
Conference
Conference  30th European Signal Processing Conference 

Abbreviated title  EUSIPCO 2022 
Country/Territory  Serbia 
City  Belgrade 
Period  29/08/22 → 2/09/22 
Internet address 
Keywords
 Computational modeling
 time series analyses
 signal processing algorithms
 Europe
 Signal processing
 ENTROPY
 Time measurement
 Permutation entropy
 graph signals
 entropy metrics
 complexity
 Multivariate Time Series
Fingerprint
Dive into the research topics of 'Multivariate permutation entropy, a Cartesian graph product approach'. 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