TY  - CONF
ID  - SisLab1766
UR  - http://www.icassp2016.org
A1  - Nguyen, Viet Dung
A1  - Abed-Meraim, Karim
A1  - Nguyen, Linh Trung
Y1  - 2016/03/20/
N2  - We present a fast adaptive PARAFAC decomposition algorithm with low computational complexity. The proposed algorithm generalizes the Orthonormal Projection Approximation Subspace Tracking (OPAST) approach for tracking a class of third-order tensors which have one dimension growing with time. It has linear complexity, good convergence rate and good estimation accuracy. To deal with large-scale problems, a parallel implementation can be applied to reduce both computational complexity and storage. We illustrate the effectiveness of our algorithm in comparison with the state-of-the-art algorithms through simulation experiments.
TI  - Fast adaptive PARAFAC decomposition algorithm with linear complexity
SP  - 6235
M2  - China
AV  - public
EP  - 6239
T2  - 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ER  -