Iterative methods for solving tensor equations based on exponential acceleration

The tensor equation A x m - 1 = b with the tensor A of order m and dimension n and the vector b , has practical applications in several fields including signal processing, high-dimensional PDEs, high-order statistics, and so on. In this paper, a class of exponential accelerated iterative methods is...

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Veröffentlicht in:Numerical algorithms 2024-09, Vol.97 (1), p.29-49
Hauptverfasser: Liang, Maolin, Dai, Lifang, Zhao, Ruijuan
Format: Artikel
Sprache:eng
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Zusammenfassung:The tensor equation A x m - 1 = b with the tensor A of order m and dimension n and the vector b , has practical applications in several fields including signal processing, high-dimensional PDEs, high-order statistics, and so on. In this paper, a class of exponential accelerated iterative methods is proposed for solving the tensor equation mentioned above in the sense that the coefficient tensor A is a symmetric and nonsingular or singular M -tensor. The obtained iterative schemes involve the classical Newton’s method as a special case. It is shown that the proposed method for nonsingular case is superlinearly convergent, while for singular cases, it is linearly convergent. The performed numerical experiments demonstrate that our methods outperform some existing ones.
ISSN:1017-1398
1572-9265
DOI:10.1007/s11075-023-01692-w