关键词: 张量填充, 低秩 Toeplitz 张量, 随机算法

Abstract: In this paper, we consider the solution for the completion problem of low rank Toeplitz tensors , and based on the high-accuracy completion algorithm, present a high-accuracy completion algorithm with randomized technique, in which the n-mode tensor is stochastically unfolded and the corresponding singular value decomposition (SVD) is modified in each iteration. Moreover, the convergence of the new algorithm is established. The results of numerical experiments on the Toeplitz tensor and the Toeplitz mean tensor show that the new algorithm is significantly better than the high-accuracy completion algorithm for low rank Toeplitz tensors in terms of computational cost.