@inproceedings{SisLab3700,
       booktitle = {2019 KICS Korea-Vietnam International Joint Workshop on Communications and Information Sciences},
           month = {November},
           title = {EEG tensor representation using graph signal processing},
          author = {Thanh Xuyen Le and Trung Thanh Le and Linh Trung Nguyen and Thi Thuy Quynh Tran and Duc Thuan Nguyen},
            year = {2019},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3700/},
        abstract = {To help analyze electroencephalography (EEG) data for epilepsy, we propose a temporal?spatial?spectral tensor tensor representation for epileptic spikes via graph signal processing. Instead of using the temporal behavior of the sources, we apply the graph wavelet transform to the spatial variable for constructing the new representation of the epilepsy tensor, in order to exploit latent information of the spatial domain. To illustrate the usefulness of the proposed method for EEG tensor representation, we decompose this tensor to separate EEG sources. Simulation results on real EEG data of a patient diagnosed of epilepsy indicated that our proposed method of representation is promising in estimating the epileptic sources.}
}