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- W2516324901 abstract "In this paper, the dynamic characteristic of electroencephalogram (EEG) is concerned by using the multiscale permutation entropy (MPE) as a measure. Meanwhile, adaptive neuro-fuzzy inference system (ANFIS) is applied to evaluate the performance of the above measures to identify the complex EEG groups. The experimental results show that, based on the MPE measures, the classification rate is 64.8%, which is much higher than 35.4%, that is get with only single-scale PE method. Experimental results show that the feature extraction of EEG signals based on MPE can uncover the hidden characteristics of EEG signals." @default.
- W2516324901 created "2016-09-16" @default.
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- W2516324901 date "2016-05-01" @default.
- W2516324901 modified "2023-09-26" @default.
- W2516324901 title "The classification based on ANFIS for EEG recordings" @default.
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- W2516324901 doi "https://doi.org/10.1109/ccdc.2016.7531516" @default.
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