Cargando…
EEG-Based Emotion Recognition Using an Improved Weighted Horizontal Visibility Graph
Emotion recognition, as a challenging and active research area, has received considerable awareness in recent years. In this study, an attempt was made to extract complex network features from electroencephalogram (EEG) signals for emotion recognition. We proposed a novel method of constructing forw...
Autores principales: | Kong, Tianjiao, Shao, Jie, Hu, Jiuyuan, Yang, Xin, Yang, Shiyiling, Malekian, Reza |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962200/ https://www.ncbi.nlm.nih.gov/pubmed/33800116 http://dx.doi.org/10.3390/s21051870 |
Ejemplares similares
-
Fusion Graph Representation of EEG for Emotion Recognition
por: Li, Menghang, et al.
Publicado: (2023) -
Analysis of alcoholic EEG signals based on horizontal visibility graph entropy
por: Zhu, Guohun, et al.
Publicado: (2014) -
Cross-Subject EEG Emotion Recognition With Self-Organized Graph Neural Network
por: Li, Jingcong, et al.
Publicado: (2021) -
Multiscale limited penetrable horizontal visibility graph for analyzing nonlinear time
series
por: Gao, Zhong-Ke, et al.
Publicado: (2016) -
Analysis of Air Mean Temperature Anomalies by Using Horizontal Visibility Graphs
por: Gómez-Gómez, Javier, et al.
Publicado: (2021)