Görsel Uyaranlara İlişkin Manyetoensefalografi Sinyallerinin Genelleştirilmiş Regresyon Sinir Ağı ile Sınıflandırılması
Objective: The aim of this study is to classify the magnetoencephalography (MEG) signals with artificial neural network to solve brain activity. Methods: The Generalized Regression Neural Network (GRNN) was used to classify MEG signals. The features of the signals were extracted by the Riemannian a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Dicle University Medical School
2019-03-01
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| Series: | Dicle Medical Journal |
| Subjects: | |
| Online Access: | http://diclemedj.org/upload/sayi/72/Dicle%20Med%20J-03563.pdf |