%0 Conference Paper
%A Nguyen, Viet Dung
%A Abed-Meraim, Karim
%A Nguyen, Linh Trung
%B 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
%C China
%D 2016
%F SisLab:1766
%P 6235-6239
%T Fast adaptive PARAFAC decomposition algorithm with linear complexity
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1766/
%X 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.