@inproceedings{SisLab2947,
       booktitle = {12th International Symposium on Medical Information and Communication Technology (ISMICT)},
           month = {March},
           title = {A Non-Linear Tensor Tracking Algorithm for Analysis of Incomplete Multi-Channel EEG Data},
          author = {Linh Trung Nguyen and Minh Chinh Truong and Viet Dung Nguyen and Karim Abed-Meraim},
            year = {2018},
           pages = {114--119},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2947/},
        abstract = {Tensor decomposition is a popular tool to analyse and process data which can be represented by a higher-order
tensor structure. In this paper, we consider tensor  tracking in challenging situations where the observed data are streaming and incomplete. Specifically, we proposed a non-linear formulation of the PETRELS cost function and based on which we proposed NL-PETRELS subspace and tensor tracking algorithms. The non-linear function allows us to improve the convergence rate. We also illustrated the use of our proposed tensor tracking for incomplete multi-channel electroencephalogram (EEG) data in a real-life experiment in which the data can be represented by a third-order tensor.}
}