Generalized Singular Value Decompositions for Tensors and Their Applications

Generalized Singular Value Decompositions for Tensors and Their Applications

Year:    2021

Author:    Chao Zeng, Zhuo-Heng He, Michael K. Ng, Chao Zeng

Numerical Mathematics: Theory, Methods and Applications, Vol. 14 (2021), Iss. 3 : pp. 692–713

Abstract

In this paper, we consider the generalized singular value decompositions for two tensors via the T-product. We investigate and discuss in detail the structures of the quotient singular value decomposition (T-QSVD) and product singular value decomposition (T-PSVD) for two tensors. The algorithms are presented with numerical examples illustrating the results. For applications, we consider color image watermarking processing with T-QSVD and T-PSVD. There are two advantages to T-QSVD and T-PSVD approaches on color watermark processing: two color watermarks can be processed simultaneously and only one key needs to be saved.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/nmtma.OA-2020-0132

Numerical Mathematics: Theory, Methods and Applications, Vol. 14 (2021), Iss. 3 : pp. 692–713

Published online:    2021-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    22

Keywords:    Multilinear algebra singular value decomposition tensor SVD.

Author Details

Chao Zeng

Zhuo-Heng He

Michael K. Ng

Chao Zeng

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