An Enhanced Numerical Iterative Method for Expanding the Attraction Basins When Computing Matrix Signs of Invertible Matrices

Author:

Shi Lei1ORCID,Ullah Malik2ORCID,Nashine Hemant3,Alansari Monairah2,Shateyi Stanford4ORCID

Affiliation:

1. School of Mathematics and Statistics, Anyang Normal University, Anyang 455002, China

2. Mathematical Modelling and Applied Computation (MMAC) Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia

3. Mathematics Division, School of Advanced Sciences and Languages, VIT Bhopal University, Bhopal-Indore Highway, Kothrikalan, Sehore 466114, Madhya Pradesh, India

4. Department of Mathematics and Applied Mathematics, School of Mathematical and Natural Sciences, University of Venda, Private Bag X5050, Thohoyandou 0950, South Africa

Abstract

The computation of the sign function of a matrix plays a crucial role in various mathematical applications. It provides a matrix-valued mapping that determines the sign of each eigenvalue of a nonsingular matrix. In this article, we present a novel iterative algorithm designed to efficiently calculate the sign of an invertible matrix, emphasizing the enlargement of attraction basins. The proposed solver exhibits convergence of order four, making it highly efficient for a wide range of matrices. Furthermore, the method demonstrates global convergence properties. We validate the theoretical outcomes through numerical experiments, which confirm the effectiveness and efficiency of our proposed algorithm.

Funder

Deanship of Scientific Research

Publisher

MDPI AG

Subject

Statistics and Probability,Statistical and Nonlinear Physics,Analysis

Reference27 articles.

1. Hogben, L. (2007). Handbook of Linear Algebra, Chapman and Hall/CRC.

2. Linear model reduction and solution of the algebraic Riccati equation by use of the sign function;Roberts;Int. J. Cont.,1980

3. Higham, N.J. (2008). Functions of Matrices: Theory and Computation, Society for Industrial and Applied Mathematics.

4. A family of Chaplygin–type solvers for Itô stochastic differential equations;Soheili;Appl. Math. Comput.,2019

5. A scaling and squaring algorithm for the matrix exponential;Higham;SIAM J. Matrix Anal. Appl.,2009

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