A fast correction approach to tensor robust principal component analysis

• Main Authors: Zhang, Zhechen, Liu, Sanyang, Lin, Zhiping, Xue, Jize, Liu, Lixia
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Article
• 語言: English
• 出版: 2024
• 主題: Engineering; Tensor nuclear norm; Tensor singular value decomposition
• 在線閱讀: https://hdl.handle.net/10356/180347
• 機構: 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 (...