Two-sided randomized algorithms for approximate K-term t-SVD

被引:0
|
作者
Wang, Xuezhong [1 ]
Hou, Shuai [1 ]
Wang, Kai [1 ,2 ]
机构
[1] Hexi Univ, Sch Math, Zhangye 734000, Peoples R China
[2] Jiashan Fudan Inst, Jiaxing 314100, Peoples R China
基金
中国国家自然科学基金;
关键词
Tensor-tensor product; t-SVD; Randomized t-SVD; Two-side randomized t-SVD; TENSOR; TUCKER; DECOMPOSITIONS; FACTORIZATION; MATRICES;
D O I
10.1016/j.aml.2024.109198
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper is devoted to the computation of the approximate K-term t-SVD of third-order tensors via random techniques. With a given truncated term K, we obtain the two-side randomized algorithms for the approximate K-term t-SVD, denoted by two-sided randomized t-SVD. Furthermore, we delve into the deterministic and probabilistic error bounds, considering specific presumptions regarding the proposed algorithm. Additionally, we integrate the current algorithm with the power method to enhance the precision of the approximate K-term t-SVD. To demonstrate the effectiveness of our proposed algorithm, we present several numerical examples.
引用
收藏
页数:6
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