BCI-HCI-IITKGP / Weighted-Sparse-classification

Classification of MI EEG signal using weighted sparsity approach

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MI-classification-using-weighted sparsity

Classification of Motor Imagery EEG signal using weighted sparsity approach

Dataset used:

Dataset IVa from BCI competition III http://www.bbci.de/competition/iii.

Installation

This project is implemented in python 2.7.

To make easier the installation of Python dependencies, we recommend the Anaconda Python distribution.

We recommend to install jupyter notebook.

In addition, the knowledge base for EEG interpretation depends on the following packages:

scipy
scikit-learn
pywt
wyrm

To support visualization of the interpretation results use matplotlib package.

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Classification of MI EEG signal using weighted sparsity approach


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