Browsing Sazali Yaacob, Prof. Dr. by Subject "LDA"
Now showing items 1-4 of 4
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Appraising human emotions using time frequency analysis based EEG alpha band features
(Institute of Electrical and Electronics Engineering (IEEE), 2009-07-25)In recent years, assessing human emotions through Electroencephalogram (EEG) is become one of the active research area in Brain Computer Interface (BCI) development. The combination of surface Laplacian filtering, ... -
Classification of speech dysfluencies with MFCC and LPCC features
(Elsevier Ltd., 2012-02)The goal of this paper is to discuss comparison of speech parameterization methods: Mel-Frequency Cepstrum Coefficients (MFCC) and Linear Prediction Cepstrum Coefficients (LPCC) for recognizing the stuttered events. Speech ... -
Comparison of different wavelet features from EEG signals for classifying human emotions
(Institute of Electrical and Electronics Engineering (IEEE), 2009-10-04)In recent years, estimation of human emotions from Electroencephalogram (EEG) signals plays a vital role on developing intellectual Brain Computer Interface (BCI) devices. In this work, we have collected the EEG signals ... -
Modified energy based time-frequency features for classifying human emotions using EEG
(Universiti Malaysia Perlis, 2009-10-11)In this paper we summarize the emotion recognition from the electroencephalogram (EEG) signals. The combination of surface Laplacian filtering, time-frequency analysis (Wavelet Transform) and linear classifiers are used ...