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Multivariate Multiscale Entropy for Brain Consciousness Analysis

Ahmed, Mosabber Uddin and Li, Ling and Cao, Jianting and Mandic, Danilo P. (2011) Multivariate Multiscale Entropy for Brain Consciousness Analysis. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, pp. 182-196. ISBN 978-1-4244-4121-1. E-ISBN 978-1-4577-1589-1. (doi:10.1109/IEMBS.2011.6090185) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/IEMBS.2011.6090185

Abstract

The recently introduced multiscale entropy (MSE) analysis accounts for the complexity over multiple time scales and therefore can reveal the complex structure of the biological signal. The existing MSE algorithm deals with scalar time series whereas multivariate time series are common in experimental and biological systems. To that cause, the MSE method is extended to multivariate case in this paper. Simulation results to characterize brain consciousness supports the efficiency of this holistic approach.

Item Type: Book section
DOI/Identification number: 10.1109/IEMBS.2011.6090185
Uncontrolled keywords: entropy; time series analysis; electroencephalography; complexity theory; white noise; vectors
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Faculties > Sciences > School of Computing > Data Science
Depositing User: Caroline Li
Date Deposited: 21 Sep 2012 09:49 UTC
Last Modified: 19 Sep 2019 14:58 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/30735 (The current URI for this page, for reference purposes)
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