scholarly journals A fast and stable test to check if a weakly diagonally dominant matrix is a nonsingular M-matrix

2018 ◽  
Vol 88 (316) ◽  
pp. 783-800 ◽  
Author(s):  
Parsiad Azimzadeh

2013 ◽  
Vol 7 ◽  
pp. 2111-2116
Author(s):  
Zhi-Jun Guo ◽  
Xu-Hui Shen ◽  
Yu-Ming Chu


2012 ◽  
Vol 2012 ◽  
pp. 1-16
Author(s):  
Guangbin Wang ◽  
Ting Wang ◽  
Yanli Du

We present some sufficient conditions on convergence of AOR method for solvingAx=bwithAbeing a strictly doublyαdiagonally dominant matrix. Moreover, we give two numerical examples to show the advantage of the new results.



Author(s):  
María Mendoza ◽  
Marcos Raydan ◽  
Pablo Tarazaga


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Guangbin Wang ◽  
Ting Wang

We discuss the convergence of the GAOR method to solve linear system which occurred in solving the weighted linear least squares problem. Moreover, we present one convergence theorem of the GAOR method when the coefficient matrix is a strictly doublyαdiagonally dominant matrix which is a nonsingularH-matrix. Finally, we show that our results are better than previous ones by using four numerical examples.



2019 ◽  
Vol 11 (6) ◽  
pp. 1
Author(s):  
Xin Li ◽  
Mei Qin

In this paper, we present a new practical criteria for H-matrix based on γ-diagonally dominant matrix. In order to make the judgment conditions convenient and effective, we give two new definitions, one is called strong and weak diagonally dominant degree, the other is called the sum of non-principal diagonal element for the matrix. Further, we obtain a new practical method for the determination of the H-matrix by combining the properties of γ-diagonally dominant matrix, constructing positive diagonal matrix, and adding the appropriate parameters. Finally, we offer numerical examples to verify the validity of the judgment conditions, corresponding numerical examples compared the new criteria and the existing results are presented to verify the advantages of the new determination method.



2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Gashaye Dessalew ◽  
Tesfaye Kebede ◽  
Gurju Awgichew ◽  
Assaye Walelign

In this paper, we present refinement of multiparameters overrelaxation (RMPOR) method which is used to solve the linear system of equations. We investigate its convergence properties for different matrices such as strictly diagonally dominant matrix, symmetric positive definite matrix, and M-matrix. The proposed method minimizes the number of iterations as compared with the multiparameter overrelaxation method. Its spectral radius is also minimum. To show the efficiency of the proposed method, we prove some theorems and take some numerical examples.



2002 ◽  
Vol 79 (7) ◽  
pp. 841-848 ◽  
Author(s):  
Xijuan Guo ◽  
Zhihua Liu Chao Jia ◽  
Chao Jia


2021 ◽  
Vol 4 (1) ◽  
pp. 53-61
Author(s):  
KJ Audu ◽  
YA Yahaya ◽  
KR Adeboye ◽  
UY Abubakar

Given any linear stationary iterative methods in the form z^(i+1)=Jz^(i)+f, where J is the iteration matrix, a significant improvements of the iteration matrix will decrease the spectral radius and enhances the rate of convergence of the particular method while solving system of linear equations in the form Az=b. This motivates us to refine the Extended Accelerated Over-Relaxation (EAOR) method called Refinement of Extended Accelerated Over-Relaxation (REAOR) so as to accelerate the convergence rate of the method. In this paper, a refinement of Extended Accelerated Over-Relaxation method that would minimize the spectral radius, when compared to EAOR method, is proposed. The method is a 3-parameter generalization of the refinement of Accelerated Over-Relaxation (RAOR) method, refinement of Successive Over-Relaxation (RSOR) method, refinement of Gauss-Seidel (RGS) method and refinement of Jacobi (RJ) method. We investigated the convergence of the method for weak irreducible diagonally dominant matrix, matrix or matrix and presented some numerical examples to check the performance of the method. The results indicate the superiority of the method over some existing methods.



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