A Family of Iterative Methods for Computing Generalized Inverses of Quaternion Matrices and its Applications

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Karmakar, Biswarup, Bhadala, Neha, Behera, Ratikanta
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866911640516034560
author Karmakar, Biswarup
Bhadala, Neha
Behera, Ratikanta
author_facet Karmakar, Biswarup
Bhadala, Neha
Behera, Ratikanta
contents The computation of generalized inverses of quaternion matrices is a fundamental problem in quaternion linear algebra, with wide-ranging applications in signal processing, image restoration, and multidimensional data analysis. This paper presents three efficient quaternion iterative algorithms for computing the Moore-Penrose pseudoinverse: (i) the quaternion rapid iterative method (QRAPID), (ii) the quaternion strong approximate inverse (QSAI), and (iii) the quaternion hyperpower iterative method of order nineteen (QHPI19). Convergence theorems and perturbation bounds are established to ensure numerical stability and robustness. The QSAI method is further employed as a preconditioner for quaternion Krylov subspace solvers, resulting in substantial reductions in the iteration count and runtime for large-scale linear systems. Comprehensive numerical experiments demonstrate that the proposed algorithms achieve an accuracy comparable to or better than existing approaches, including quaternion SVD, quaternion Newton-Schulz, and classical hyperpower schemes, while offering significant computational savings. The practical utility of the framework is illustrated through two representative applications: image completion via CUR decomposition and signal filtering, which confirm its scalability and effectiveness in real-world multidimensional data applications.
format Preprint
id arxiv_https___arxiv_org_abs_2605_01464
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Family of Iterative Methods for Computing Generalized Inverses of Quaternion Matrices and its Applications
Karmakar, Biswarup
Bhadala, Neha
Behera, Ratikanta
Numerical Analysis
15A09, 15A10, 15A69, 65F20
The computation of generalized inverses of quaternion matrices is a fundamental problem in quaternion linear algebra, with wide-ranging applications in signal processing, image restoration, and multidimensional data analysis. This paper presents three efficient quaternion iterative algorithms for computing the Moore-Penrose pseudoinverse: (i) the quaternion rapid iterative method (QRAPID), (ii) the quaternion strong approximate inverse (QSAI), and (iii) the quaternion hyperpower iterative method of order nineteen (QHPI19). Convergence theorems and perturbation bounds are established to ensure numerical stability and robustness. The QSAI method is further employed as a preconditioner for quaternion Krylov subspace solvers, resulting in substantial reductions in the iteration count and runtime for large-scale linear systems. Comprehensive numerical experiments demonstrate that the proposed algorithms achieve an accuracy comparable to or better than existing approaches, including quaternion SVD, quaternion Newton-Schulz, and classical hyperpower schemes, while offering significant computational savings. The practical utility of the framework is illustrated through two representative applications: image completion via CUR decomposition and signal filtering, which confirm its scalability and effectiveness in real-world multidimensional data applications.
title A Family of Iterative Methods for Computing Generalized Inverses of Quaternion Matrices and its Applications
topic Numerical Analysis
15A09, 15A10, 15A69, 65F20
url https://arxiv.org/abs/2605.01464