On convergence of matrix and tensor approximate diagonalization algorithms by unitary transformations

Konstantin Usevich (1) , Jianze Li (2) , Pierre Comon (3)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 Ryerson University [Toronto]
3 GIPSA-CICS - GIPSA - Communication Information and Complex Systems

In this paper, we propose a gradient-based Jacobi algorithm for approximate diag-onalization of complex matrices and tensors by unitary transformations. We provide global and local convergence results for this algorithm. The convergence results also apply to the case of real-valued tensors.

Domaines: Optimisation et contrôle [math.OC]; Analyse numérique [math.NA]

Konstantin Usevich, Jianze Li, Pierre Comon. On convergence of matrix and tensor approximate diagonalization algorithms by unitary transformations. 2019. ⟨hal-01998900v1⟩