TY  - CONF
ID  - SisLab2947
UR  - http://www.ismict2018.org/
A1  - Nguyen, Linh Trung
A1  - Truong, Minh Chinh
A1  - Nguyen, Viet Dung
A1  - Abed-Meraim, Karim
Y1  - 2018/03/26/
N2  - 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.
TI  - A Non-Linear Tensor Tracking Algorithm for Analysis of Incomplete Multi-Channel EEG Data
SP  - 114
M2  - Sydney, Australia
AV  - public
EP  - 119
T2  - 12th International Symposium on Medical Information and Communication Technology (ISMICT)
ER  -