Fast adaptive PARAFAC decomposition algorithm with linear complexity

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IEEE Xplore Abstract - Fast adaptive PARAFAC decomposition algorithm with linear complexity

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<b>Fast adaptive PARAFAC</b>

<b>decomposition algorithm with linear</b>

<b>complexity</b>

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<b>Author(s)</b>

<b>Page(s):</b>

6235 - 6239

<b>Conference Location :</b>

Shanghai, China

<b>DOI:</b>

10.1109/ICASSP.2016.7472876

<b>Publisher:</b>

IEEE

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.

<b>Published in:</b>

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

<b>Date of Conference:</b>

20-25 March 2016

<b>Institutional Sign In</b>

Viet-Dung Nguyen ; PRISME Laboratory, University of Orl��ans, France ; Karim Abed-Meraim ; Nguyen Linh-Trung

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<b>Abstract</b>

6/7/16, 9:14 PM
IEEE Xplore Abstract - Fast adaptive PARAFAC decomposition algorithm with linear complexity

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