Convergence Analysis of Iterative Method for L-matrix under Preconditioned AOR
Yonghui Huang
Abstract
Yonghui Huang
Abstract
This paper is to discuss the convergence analysis of a new preconditioned AOR iterative method for L-matrix.If the coefficient matrix is a strictly dominant L-matrix,the convergence rate of the preconditioned AOR iterative method is faster than one of the AOR methods.In addition,the spectral radius of the reconditioned AOR iterative method is monotonically decreasing.In the end,some numerical examples to verify the correctness of our theoretical results are given.
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This paper is to discuss the convergence analysis of a new preconditioned AOR iterative method for L-matrix.If the coefficient matrix is a strictly dominant L-matrix,the convergence rate of the preconditioned AOR iterative method is faster than one of the AOR methods.In addition,the spectral radius of the reconditioned AOR iterative method is monotonically decreasing.In the end,some numerical examples to verify the correctness of our theoretical results are given.
Key concepts: Spectral radius, Correctness, Iterative method, Convergence (economics), Matrix (chemical analysis), Mathematics, Rate of convergence, Applied mathematics