A matching pursuit-based signal complexity measure for the analysis of newborn EEG

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A matching pursuit-based signal complexity measure for the analysis of newborn EEG

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dc.contributor.author Rankine, L
dc.contributor.author Mesbah, M
dc.contributor.author Boashash, B
dc.date.accessioned 2011-10-19T05:45:46Z
dc.date.available 2011-10-19T05:45:46Z
dc.date.issued 2007-03
dc.identifier.citation Vol. 45 Issue 3, p251-260 en_US
dc.identifier.issn 01400118
dc.identifier.other DOI: 10.1007/s11517-006-0143-0
dc.identifier.uri http://hdl.handle.net/10576/10766
dc.description This paper presents the Relative structural complexity, a new MP-based measure of signal complexity, where the relativity is associated with the chosen decomposition dictionary. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). en_US
dc.description.abstract This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity (RSC), which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed RSC measure is used in the analysis of newborn electroencephalogram (EEG). To do this, firstly, a time–frequency decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure). en_US
dc.language.iso en en_US
dc.publisher Medical & Biological Engineering & Computing en_US
dc.subject Matching pursuit en_US
dc.subject Relative structural complexity en_US
dc.subject Coherent dictionary en_US
dc.subject Time–frequency en_US
dc.subject Newborn EEG en_US
dc.subject quadratic TFDs en_US
dc.subject time-frequency distributions en_US
dc.subject Modified B-Distribution en_US
dc.subject complexity measure en_US
dc.title A matching pursuit-based signal complexity measure for the analysis of newborn EEG en_US
dc.type Article en_US

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