Weighted tensor decomposition for approximate decoupling of multivariate polynomials [article]

Gabriel Hollander, Philippe Dreesen, Mariya Ishteva, Johan Schoukens
2016 arXiv   pre-print
Multivariate polynomials arise in many different disciplines. Representing such a polynomial as a vector of univariate polynomials can offer useful insight, as well as more intuitive understanding. For this, techniques based on tensor methods are known, but these have only been studied in the exact case. In this paper, we generalize an existing method to the noisy case, by introducing a weight factor in the tensor decomposition. Finally, we apply the proposed weighted decoupling algorithm in
more » ... domain of system identification, and observe smaller model errors.
arXiv:1601.07800v1 fatcat:cyelouf5vfebdnuqicy7hdav4e