Abstract
The emotion belongs to higher nervous activity in the Cerebral cortex of human. Now many researchers use BCI in formal analysis, simulation, and phototyping to explore predicted system behavior between the subjective world of emotion and the objective world of the signal. This paper also compares various classifiers of emotion recognition, and then applies two sets of classifiers. The unsupervised classification include DBN, the supervised classification include Bayesclassifier and Fisherclassifier and SVM. The DNB method performed better than SVM in classification accruracy, and the Bayesclassifier is better than Fisherclassifier in run time. DBN has a higher classification accuracy and lower standard deviation, more suitable for EEG emotion recognition.
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Ma, X., Liu, Z., Jiang, T., Zhang, X. (2019). Study of the Algorithm for the Classification of Brain Waves. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_283
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DOI: https://doi.org/10.1007/978-981-10-6571-2_283
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