Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/1795
Title: IMPROVING PRECONDITIONED GAUSS-SEIDEL ITERATIVE METHOD FOR 𝑳 −MATRICES
Authors: Ndanusa, Abdulrahman
David, Bukola Eunice
Ayantola, Bukunmi Boluwatife
Wachin, Abdullahi Abubakar
Keywords: Gauss-Seidel method, 𝐿 −-matrix, iteration matrix, convergence, spectral radius
Issue Date: 2020
Publisher: FUDMA Journal of Sciences
Citation: Ndanusa, A., David, B. E., Ayantola, B. B. and Abubakar, A. W. (2020). IMPROVING PRECONDITIONED GAUSS-FUDMA Journal of Sciences, 4(1): 453-459.SEIDEL ITERATIVE METHOD FOR 𝑳 −MATRICES.
Abstract: The Gauss-Seidel is a well-known iterative method for solving the linear system 𝐴𝑥 = 𝑏. Convergence of this method is guaranteed for linear systems whose coefficient matrix 𝐴 is strictly or irreducibly diagonally dominant, Hermitian positive definite and invertible 𝐻 −matrix. In this current work, a preconditioned version of the Gauss-Seidel method is used to accelerate the convergence of this iterative method towards the solution of linear system 𝐴𝑥 = 𝑏 under mild conditions imposed on 𝐴. Convergence theorems on preconditioned Gauss-Seidel iterative method are advanced and proved. The superiority of Preconditioned Gauss-Seidel method is demonstrated by solving some numerical examples.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/1795
ISSN: ISSN online: 2616-1370
Appears in Collections:Mathematics

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