This project combines Conditional Generative Adversarial Networks (CCGAN) and Support Vector Machines (SVM) to classify EEG data. It aims to improve the accuracy of EEG classification by generating synthetic data to augment the training dataset.
- EEG data preprocessing
- Synthetic EEG data generation using CCGAN
- EEG data classification using SVM
- Python 3.8 or later
- TensorFlow 2.x
- scikit-learn
- numpy
- Clone the repository
- Install the required packages:
pip install -r requirements.txt - Run the main script:
python main.py
This project is licensed under the GPLv3 License.