On-Line Arithmetic Based Reprogrammable Hardware Implementation of LVQ Neural Network for Alertness Classification
Identifieur interne : 004540 ( Main/Exploration ); précédent : 004539; suivant : 004541On-Line Arithmetic Based Reprogrammable Hardware Implementation of LVQ Neural Network for Alertness Classification
Auteurs : M. Boubaker [Tunisie] ; Khaled Ben Khalifa [Tunisie] ; Bernard Girau [France] ; Mohamed Dogui [Tunisie] ; Mohamed Hédi Bedoui [Tunisie]Source :
English descriptors
Abstract
The current study presents the hardware implementation of a learning Vector Quantization (LVQ) neural network. Starting from the spectral EEG analysis, we suggest an LVQ serial on-line architecture implementation on a Field programmable Gate Array (FPGA) circuit. Our concern was mainly to get a light, easy-to-wear system for the classification of vigilance levels in humans using EEG signals. The results of these classified states by LVQ mode are presented in this paper. Furthermore, the highly satisfactory performances of our implementation in terms of area speed and delay are described.
Url:
Affiliations:
- France, Tunisie
- Grand Est, Lorraine (région)
- Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
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Tunisie</addrLine><country key="TN"></country></address><ref type="url">http://www.ltim.org/</ref></desc><listRelation><relation active="#struct-365276" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-365276" type="direct"><org type="institution" xml:id="struct-365276" status="INCOMING"><orgName>Faculté de Médecine de Monastir</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle></tutelles></hal:affiliation><country>Tunisie</country></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>EEG and vigilance</term><term>FPGA</term><term>LVQ neural network</term><term>on-line arithmetics</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The current study presents the hardware implementation of a learning Vector Quantization (LVQ) neural network. Starting from the spectral EEG analysis, we suggest an LVQ serial on-line architecture implementation on a Field programmable Gate Array (FPGA) circuit. Our concern was mainly to get a light, easy-to-wear system for the classification of vigilance levels in humans using EEG signals. The results of these classified states by LVQ mode are presented in this paper. Furthermore, the highly satisfactory performances of our implementation in terms of area speed and delay are described.</div></front></TEI><affiliations><list><country><li>France</li><li>Tunisie</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Nancy</li></settlement><orgName><li>Institut national polytechnique de Lorraine</li><li>Université Nancy 2</li><li>Université de Lorraine</li></orgName></list><tree><country name="Tunisie"><noRegion><name sortKey="Boubaker, M" sort="Boubaker, M" uniqKey="Boubaker M" first="M." last="Boubaker">M. Boubaker</name></noRegion><name sortKey="Bedoui, Mohamed Hedi" sort="Bedoui, Mohamed Hedi" uniqKey="Bedoui M" first="Mohamed Hédi" last="Bedoui">Mohamed Hédi Bedoui</name><name sortKey="Ben Khalifa, Khaled" sort="Ben Khalifa, Khaled" uniqKey="Ben Khalifa K" first="Khaled" last="Ben Khalifa">Khaled Ben Khalifa</name><name sortKey="Dogui, Mohamed" sort="Dogui, Mohamed" uniqKey="Dogui M" first="Mohamed" last="Dogui">Mohamed Dogui</name></country><country name="France"><region name="Grand Est"><name sortKey="Girau, Bernard" sort="Girau, Bernard" uniqKey="Girau B" first="Bernard" last="Girau">Bernard Girau</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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