Swamp reducing technique for tensor decomposition

C Navasca, L De Lathauwer… - 2008 16th European …, 2008 - ieeexplore.ieee.org
2008 16th European Signal Processing Conference, 2008ieeexplore.ieee.org
There are numerous applications of tensor analysis in signal processing, such as, blind
multiuser separation-equalization-detection and blind identification. As the applicability of
tensor analysis widens, the numerical techniques must improve to accommodate new data.
We present a new numerical method for tensor analysis. The method is based on the
iterated Tikhonov regularization and a parameter choice rule. Together these elements
dramatically accelerate the well-known Alternating Least-Squares method.
There are numerous applications of tensor analysis in signal processing, such as, blind multiuser separation-equalization-detection and blind identification. As the applicability of tensor analysis widens, the numerical techniques must improve to accommodate new data. We present a new numerical method for tensor analysis. The method is based on the iterated Tikhonov regularization and a parameter choice rule. Together these elements dramatically accelerate the well-known Alternating Least-Squares method.
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