A Linearly Convergent Algorithm for the H-Spectral Radius of Index-Cyclic Symmetric Positive Tensors

A class of index-cyclic symmetric positive tensors is defined, and a diagonal similarity algorithm is proposed to compute the H-spectral radius of such tensors. The linear convergence of the algorithm is rigorously proven. The computational efficiency of the proposed method is compared with that of the classical power method by numerical examples. The results indicate that the proposed algorithm achieves reliable linear convergence and offers competitive computational performance for index-cyclic symmetric positive tensors.

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Publication Details

Journal
Symmetry
Published
2026-06-18
DOI
https://doi.org/10.3390/sym18061054
Primary Topic
Tensor decomposition and applications
Type
article
Field-Weighted Citation Impact
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article

A Linearly Convergent Algorithm for the H-Spectral Radius of Index-Cyclic Symmetric Positive Tensors

Hongbin Lyu, Xincun Wang
Symmetry
Tensor decomposition and applications
article

A Linearly Convergent Algorithm for the H-Spectral Radius of Index-Cyclic Symmetric Positive Tensors

Hongbin Lyu, Xincun Wang
article en

Abstract

A class of index-cyclic symmetric positive tensors is defined, and a diagonal similarity algorithm is proposed to compute the H-spectral radius of such tensors. The linear convergence of the algorithm is rigorously proven. The computational efficiency of the proposed method is compared with that of the classical power method by numerical examples. The results indicate that the proposed algorithm achieves reliable linear convergence and offers competitive computational performance for index-cyclic symmetric positive tensors.

SymmetryVol. 18(6)
Putian University (CN), Eastern Liaoning University (CN)
Openalex Percentile: Top 5%
Tensor decomposition and applications
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