%0 Conference Paper
%A Nguyen, Linh Trung
%A Truong, Minh Chinh
%A Nguyen, Viet Dung
%A Abed-Meraim, Karim
%B 12th International Symposium on Medical Information and Communication Technology (ISMICT)
%C Sydney, Australia
%D 2018
%F SisLab:2947
%P 114-119
%T A Non-Linear Tensor Tracking Algorithm for Analysis of Incomplete Multi-Channel EEG Data
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2947/
%X 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.