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Motor Imagery EEG Signal Classification Using Random Subspace Ensemble Network

Project README

Motor Imagery EEG Classification Using Random Subspace Ensemble Network with Variable Length Features

Running Matlab Scripts: https://youtu.be/AeRMO98-URc

This is a codebase for motor imagery EEG experiments for three projects.

  1. Matlab-based baseline for EEG classification. (minimal matlab)

  2. Classification of motor imagery EEG signals with multi-input convolutional neural network by augmenting STFT. [IEEE] [PDF] Notebooks: (STFT_CNN_benchmark.ipynb, bci_4_tl_sub1.ipynb, bci_4_tl_sub2.ipynb)

  3. Motor Imagery EEG Classification Using Random Subspace Ensemble Network with Variable Length Features. [Google Scholar] [PDF] Notebooks: (result.ipynb, result_all.ipynb, result_rsenet.ipynb, result_rsenet_all.ipynb, visualization.ipynb)

Open Source Agenda is not affiliated with "Eeg Rsenet" Project. README Source: zabir-nabil/eeg-rsenet

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