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首页> 外文期刊>SIAM Journal on Numerical Analysis >Regularizing Newton-Kaczmarz methods for nonlinear ill-posed problems
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Regularizing Newton-Kaczmarz methods for nonlinear ill-posed problems

机译:正则化牛顿-Kaczmarz方法的非线性不适定问题

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We introduce a class of stabilizing Newton-Kaczmarz methods for nonlinear ill-posed problems and analyze their convergence and regularization behavior. As usual for iterative methods for solving nonlinear ill-posed problems, conditions on the nonlinearity (or the derivatives) have to be imposed in order to obtain convergence. As we shall discuss in general and in some specific examples, the nonlinearity conditions obtained for the Newton-Kaczmarz methods are less restrictive than those for previously existing iteration methods and can be verified for several practical applications. We also discuss the discretization and efficient numerical solution of the linear problems arising in each step of a Newton-Kaczmarz method, and we carry out numerical experiments for two model problems.
机译:我们针对非线性不适定问题介绍了一类稳定的Newton-Kaczmarz方法,并分析了它们的收敛性和正则化行为。通常,对于解决非线性不适定问题的迭代方法,必须施加非线性条件(或导数),以便获得收敛性。正如我们将在一般情况下和某些特定示例中讨论的那样,与以前存在的迭代方法相比,使用Newton-Kaczmarz方法获得的非线性条件的限制较少,并且可以在一些实际应用中得到验证。我们还讨论了牛顿-Kaczmarz方法每一步中产生的线性问题的离散化和有效数值解,并对两个模型问题进行了数值实验。

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