A new approach for classification of EEG signals [EEG sinyallerinin siniflandirilmasinda yeni bir yaklaşim]

dc.contributor.authorTezel G.
dc.contributor.authorÖzbay Y.
dc.date.accessioned2020-03-26T17:18:48Z
dc.date.available2020-03-26T17:18:48Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.description2007 IEEE 15th Signal Processing and Communications Applications, SIU -- 11 June 2007 through 13 June 2007 -- Eskisehir -- 73089en_US
dc.description.abstractThis study presents a comparative study of the classification accuracy and speed of performance of epileptic Electroensefalogram (EEG) signals using a traditional neural network architecture based on backpropagation training algorithm, and a new neural network. The proposed network is called adaptive neural network with activation function (AAF-NN) in which adjustable parameters, It is used two different activation functions for developed study. One of theese adaptive activation functions is sigmoid function with free parameters and the other one is sum of sinusoidal function with free parameters and sigmoid function with free parameters. The adaptive activation function with free parameters is used in the hidden layer for the proposed structures based on the feed-forward neural network Experimental results have revealed that neural network with adaptive activation function is more suitable for classification EEG signals and training speed is much faster than traditional neural network with fixed sigmoid activation function.en_US
dc.identifier.doi10.1109/SIU.2007.4298603en_US
dc.identifier.isbn1424407192; 9781424407194
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://dx.doi.org/10.1109/SIU.2007.4298603
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21741
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.relation.ispartof2007 IEEE 15th Signal Processing and Communications Applications, SIUen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleA new approach for classification of EEG signals [EEG sinyallerinin siniflandirilmasinda yeni bir yaklaşim]en_US
dc.typeConference Objecten_US

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