On the efficiency of LSTM in classifying musical impressions from EEG recordings
Yükleniyor...
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/restrictedAccess
Özet
The objective of this study is the classification of musical impressions with long short-term memory (LSTM) approach using EEG recordings of 20 subjects, while listening to different music genres. For this purpose, a deep learning model was developed, where relevant features extracted from intrinsic mode functions (IMF) of the clean EEG data are used as the input signals. The classification accuracy of the proposed model is evaluated with various feature sets. The highest classification accuracy is 73.33%, which is achieved by combining higher-order statistics and the first difference of IMF features.
Açıklama
Anahtar Kelimeler
Kaynak
6th International Conference of Mathematical Sciences (ICMS 2022)
WoS Q Değeri
Scopus Q Değeri
Cilt
2879
Sayı
1
Künye
Kaya, B., Habiboğlu, Mehmet G., Moghaddamnia, S. (2022). On the efficiency of LSTM in classifying musical impressions from EEG recordings. 6th International Conference of Mathematical Sciences (ICMS 2022), 2879 (1).
