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Modified Newton-DSS method for solving a class of systems of nonlinear equations with complex symmetric Jacobian matrices

机译:改进的牛顿DSS方法,用于解决复杂对称雅各比矩阵的非线性方程类别的方法

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摘要

Double-step scale splitting (DSS) iteration method is proved to be an unconditionally convergent iteration method, which is also efficient and robust for solving a class of large sparse complex symmetric systems of linear equations. In this paper, by making use of the DSS iteration technique as the inner solver to approximately solve the Newton equations, we establish a new modified Newton-DSS method for solving systems of nonlinear equations whose Jacobian matrices are large, sparse, and complex symmetric. Subsequently, we investigate the local and semilocal convergence properties of our method under some proper assumptions. Finally, numerical results on some problems illustrate the superiority of our method over some previous methods.
机译:被证明,双步比例分离(DSS)迭代方法是无条件的收敛迭代方法,其还用于求解一类线性方程的大型稀疏复杂对称系统的高效且稳健。 在本文中,通过利用DSS迭代技术作为内部求解器来大致解决牛顿方程,我们建立了一种新的改进的Newton-DSS方法,用于求解雅各的矩阵大,稀疏和复杂对称的非线性方程式的系统。 随后,我们在某种适当的假设下调查我们方法的局部和半透明会聚特性。 最后,一些问题的数值结果说明了我们对某些先前方法的方法的优越性。

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