Orthogonal Tensor Recovery Based on Non-Convex Regularization and Rank Estimation

In this paper, a method for orthogonal tensor recovery based on non-convex regularization and rank estimation (OTRN-RE) is proposed, which aims to accurately recover the low-rank and sparse components of the tensor. Specifically, a new low-rank tensor decomposition algorithm is designed, which can e...

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Autors principals:	Xixiang Chen, Jingjing Zheng, Li Zhao, Wei Jiang, Xiaoqin Zhang
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2024-01-01
Col·lecció:	IEEE Access
Matèries:	Orthogonal tensor recovery non-convex regularization tensor decomposition low-rank recovery
Accés en línia:	https://ieeexplore.ieee.org/document/10388352/
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