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dc.contributor.authorPhuong, TDen_NZ
dc.contributor.authorGriffin, Aen_NZ
dc.contributor.authorLi, XJen_NZ
dc.date.accessioned2019-01-24T22:36:48Z
dc.date.available2019-01-24T22:36:48Z
dc.date.copyright2018-07-17en_NZ
dc.identifier.citationIn 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 3108-3111). IEEE.
dc.identifier.urihttp://hdl.handle.net/10292/12192
dc.description.abstractElectroencephalogram (EEG) signals have been widely used to analyze brain activities so as to diagnose certain brain-related diseases. They are usually recorded for a fairly long interval with adequate resolution, consequently requiring a considerable amount of memory space for storage and transmission. Recently compressed sensing (CS) has been proposed in order to effectively compress EEG signals. However, its performance is closely dependent on how a compression dictionary is built. Through our study, we notice that building the best fit over-complete Gabor dictionary plays an important role in this task. In this paper, we evaluate the effect of different time and frequency step sizes in building Gabor atoms on the performance of EEG signal compression using CS with three common EEG databases used by the research community. Taking the Normalized Mean Square Error (NMSE) as a performance metric, we present a quantitative study with an attempt to provide more insight on how to adopt CS in EEG signal compression.
dc.publisherIEEE
dc.relation.urihttps://ieeexplore.ieee.org/document/8513071
dc.rightsCopyright © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.titleCompressed Sensing of EEG with Gabor Dictionary: Effect of Time and Frequency Resolutionen_NZ
dc.typeConference Contribution
dc.rights.accessrightsOpenAccessen_NZ
dc.identifier.doi10.1109/EMBC.2018.8513071
pubs.elements-id337797
aut.relation.conferenceThe 40th international Conference of the IEEE Engineering in Medicine and Biology Societyen_NZ


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