Adaptive dual-graph learning joint feature selection for EEG emotion recognition

Emotion recognition based on electroencephalography (EEG) has garnered increasing attention for its ability to reflect human emotional states objectively and in real time. However, EEG signals exhibit significant variations across different subjects and experimental sessions, posing challenges to th...

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Veröffentlicht in:	Journal of King Saud University. Computer and information sciences Jg. 37; H. 4; S. 69 - 19
Hauptverfasser:	Hu, Liangliang, Tan, Congming, Tian, Yin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.06.2025 Springer Nature B.V Springer
Schlagworte:	Adaptation Algorithms Biomarkers Brain research Cognition Computer Imaging Computer Science Database Management EEG Electroencephalography Emotion recognition Emotional factors Emotions Feature selection Global structure graph Invariants Labels Local similarity graph Machine Learning Optimization Original Paper Pattern Recognition and Graphics Physiology Propagation Regularization Software Engineering/Programming and Operating Systems Systems and Data Security Theory of Computation Vision Emotion recognition Feature selection Global structure graph EEG Local similarity graph
ISSN:	1319-1578, 2213-1248, 1319-1578
Online-Zugang:	Volltext
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