dc.contributor.advisor | Bang, Børre | |
dc.contributor.author | Lin, Jiaxin | |
dc.date.accessioned | 2017-08-25T06:37:31Z | |
dc.date.available | 2017-08-25T06:37:31Z | |
dc.date.issued | 2017-06-13 | |
dc.description.abstract | This thesis presents a brief introduction to epilepsy diagnosis use convolution neutral network. The datasets create through Electroencephao-graph(EEG) signal.Electroencephao-graph(EEG) is one of the most commonly signals recorded from humans like electrocardiogram(ECG). In this thesis give a short introduce about the EEG signal. Because EEG recordings are important in the diagnosis of epilepsy. But there is not a good way to classification these EEG signal. This paper aims to develop epileptic EEG signal classification method. | en_US |
dc.identifier.uri | https://hdl.handle.net/10037/11382 | |
dc.language.iso | eng | en_US |
dc.publisher | UiT Norges arktiske universitet | en_US |
dc.publisher | UiT The Arctic University of Norway | en_US |
dc.rights.accessRights | openAccess | en_US |
dc.rights.holder | Copyright 2017 The Author(s) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/3.0 | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) | en_US |
dc.subject.courseID | SHO6264 | |
dc.subject | VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 | en_US |
dc.subject | VDP::Technology: 500::Information and communication technology: 550 | en_US |
dc.subject | CNN EEG-signal | en_US |
dc.title | Classification of electroncephao-graph signals by convolutional neural network | en_US |
dc.type | Master thesis | en_US |
dc.type | Mastergradsoppgave | en_US |