A fast correction approach to tensor robust principal component analysis

• Main Authors: Zhang, Zhechen, Liu, Sanyang, Lin, Zhiping, Xue, Jize, Liu, Lixia
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering; Tensor nuclear norm; Tensor singular value decomposition
• Online Access: https://hdl.handle.net/10356/180347
• Institution: Nanyang Technological University

Tensor robust principal component analysis (TRPCA) is a useful approach for obtaining low-rank data corrupted by noise or outliers. However, existing TRPCA methods face certain challenges when it comes to estimating the tensor rank and the sparsity accurately. The commonly used tensor nuclear norm (...