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About Subject Independent Emotion Recognition From EEG Using VMD and Deep Learning
This document summarizes a research paper that proposes a subject independent emotion recognition technique from EEG signals. The technique uses Variational Mode Decomposition (VMD) for feature extraction and a Deep Neural Network as the classifier. VMD is used to decompose the EEG signals into intrinsic mode functions (IMFs). Features like peak power spectral density and first difference of the signal are then calculated for each IMF. These features are fed into the Deep Neural Network to classify emotions in a subject independent manner. The proposed method is evaluated using the DEAP dataset and is shown to perform better than state-of-the-art techniques for subject-independent emotion recognition from EEG.
Detailed Information
| Author: | ['NADIA TASNIM MIM'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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