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Research Article | Open Access

Tensor Conjugate-Gradient methods for tensor linear discrete ill-posed problems

Hong-Mei Song1,2Shi-Wei Wang1,2Guang-Xin Huang2,3( )
College of Mathematical and physics, Chengdu University of Technology, Chengdu, China
Sichuan Geomathematics Key Laboratory, Chengdu University of Technology, Chengdu, China
College of Computer Science and Cyber Security, Chengdu University of Technology, Chengdu, China
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Abstract

This paper presents three types of tensor Conjugate-Gradient (tCG) methods for solving large-scale linear discrete ill-posed problems based on the t-product between third-order tensors. An automatic determination strategy of a suitable regularization parameter is proposed for the tCG method in the Fourier domain (A-tCG-FFT). An improved version and a preconditioned version of the tCG method are also presented. The discrepancy principle is employed to determine a suitable regularization parameter. Several numerical examples in image and video restoration are given to show the effectiveness of the proposed tCG methods.

CLC number: 15A69, 65F05, 65J20

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AIMS Mathematics
Pages 26782-26800

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Cite this article:
Song H-M, Wang S-W, Huang G-X. Tensor Conjugate-Gradient methods for tensor linear discrete ill-posed problems. AIMS Mathematics, 2023, 8(11): 26782-26800. https://doi.org/10.3934/math.20231371

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Received: 09 July 2023
Revised: 02 September 2023
Accepted: 05 September 2023
Published: 15 November 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)