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首页> 外文期刊>International Journal of Engineering Research and Applications >Analysis of Convergence of Jacobi and Gauss Siedel Method and Error Minimization.
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Analysis of Convergence of Jacobi and Gauss Siedel Method and Error Minimization.

机译:雅各比和高斯赛德尔方法收敛分析及误差最小化。

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摘要

In this research, we will show that neither of the iterative methods always converges. Implying that the Jacobi and Gauss Seidel Methods do not converge often when applied to a system of linear equations yielding a divergent sequence of approximations. In such cases, the method is termed divergent. Therefore for a system of equations to converge, the Diagonal Dominance of the matrix is necessary before applying any iterative method. The error reduction factor will also be discussed in each Iteration in Jacobi and Gauss Seidel method.
机译:在这项研究中,我们将表明既不迭代方法始终会收敛。暗示Jacobi和Gauss Seidel方法不会在应用于线性方程系统时不收敛,产生发散近似序列。在这种情况下,该方法被称为发散。因此,对于汇聚的方程系统,在应用任何迭代方法之前需要矩阵的对角线优势。还将在Jacobi和Gauss Seidel方法中的每次迭代中讨论误差减少因子。

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