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Browse Conference Publications > 2016 IEEE International Confe
Fast adaptive PARAFAC
decomposition algorithm with linear
complexity
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Author(s)
Page(s):
6235 - 6239
Conference Location :
Shanghai, China
DOI:
10.1109/ICASSP.2016.7472876
Publisher:
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
Published in:
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Date of Conference:
20-25 March 2016
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Viet-Dung Nguyen ; PRISME Laboratory, University of Orl��ans, France ; Karim Abed-Meraim ; Nguyen Linh-Trung
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