Extracting features using computational cerebellar model for emotion classification
Several feature extraction techniques have been employed to extract features from EEG signals for classifying emotions. Such techniques are not constructed based on the understanding of EEG and brain functions, neither inspired by the understanding of emotional dynamics. Hence, the features are diff...
Main Authors: | Yaacob, Hamwira Sakti, Abdul Rahman, Abdul Wahab, Kamaruddin, Norhaslinda |
---|---|
Format: | Conference or Workshop Item |
Language: | English English |
Published: |
2013
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/38073/ http://irep.iium.edu.my/38073/ http://irep.iium.edu.my/38073/1/Extracting_features_using_computational_cerebellar_model_for_emotion_classification.pdf http://irep.iium.edu.my/38073/4/38073_Extracting%20features%20using_Scopus.pdf |
Similar Items
-
Cultural dependency analysis for understanding speech emotion
by: Kamaruddin, Norhaslinda, et al.
Published: (2012) -
Emotion recognition using electroencephalogram signal
by: Mohammad Yosi, Aqila Nur Nadira, et al.
Published: (2019) -
CMAC-Based Computational Model of Affects (CCMA) from self-organizing feature mapping weights for classification of
emotion using EEG signals
by: Yaacob, Hamwira Sakti, et al.
Published: (2015) -
Brain Topographic Mapping of Emotions using Computational Cerebellum
by: Yaacob, Hamwira Sakti, et al.
Published: (2013) -
Distinctive features for classification of respiratory sounds between normal and crackles using cepstral coefficients
by: Mohd Johari, Nabila Husna, et al.
Published: (2018)