Swamp reducing technique for tensor decomposition

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.