Main Article Content
Emotional recognition from the EEG signal is one of the areas in which many scientists around the world have concerned. Two important issues are EEG feature extraction and EEG classification. The wavelet transform method allows the extraction of nonlinear characteristics of the data from which it is possible to derive smaller feature vector than other methods. The MLP neural network has proven to be a very effective classification method. Thus, in this paper, the authors present one method to construct a highly accurate emotional recognition system by combining the two above methods. The results based on Matlab simulations with the standard data from the international scientific community.
How to Cite
Huy Nguyen , P., May Duong , T., Huong Nguyen , T., & Thuong Duong, . T. M. (2018). Combination of Wavelet and MLP Neural Network for Emotion Recognition System. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(11), 105–109. Retrieved from https://www.ijfrcsce.org/index.php/ijfrcsce/article/view/1798