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Title: Comparison of LDA and RBF-NN in EEG features classification for motor imagery [articol]
Authors: Cososchi, Ştefan
Strungaru, Rodica
Ungureanu, Mihaela G.
Subjects: EEG
Neuro-fuzzy network
Auto adaptation
Issue Date: 2006
Publisher: Timişoara: Editura Politehnica
Citation: Cososchi, Ștefan. Comparison of LDA and RBF-NN in EEG features classification for motor imagery. Timişoara: Editura Politehnica, 2006
Series/Report no.: Seria electronică şi telecomunicaţii, Tom 51(65), fasc. 1 (2006);
Abstract: This paper presents an approach that uses self-organizing fuzzy neural network based time series prediction to extract the EEG features in time domain. EEG signals from two electrodes placed on the scalp over the motor cortex are predicted by a single fuzzy neural network. Features derived from the mean squared error of the predictions and from the mean squared of the predicted signals are extracted from EEG data within a sliding window using two auto-organizing fuzzy neural networks with multi inputs and a single output. The features are classified by linear discriminant analysis and radial-basis function neural network.
URI: http://localhost:8080/xmlui/handle/123456789/1531
Appears in Collections:Articole stiintifice/Scientific articles

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