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Phase reconstruction by a multilevel iteratively regularized Gauss-Newton method

机译:多级迭代正则化高斯-牛顿法进行相位重建

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摘要

In this paper we consider the numerical solution of a phase retrieval problem for a compactly supported, linear spline f : R -> C with the Fourier transform (f) over cap , where values of vertical bar f vertical bar and vertical bar (f) over cap vertical bar at finitely many equispaced nodes are given. The unknown phases of complex spline coefficients fulfil a well-structured system of nonlinear equations. Thus the phase reconstruction leads to a nonlinear inverse problem, which is solved by a multilevel strategy and iterative Tikhonov regularization. The multilevel strategy concentrates the main effort of the solution of the phase retrieval problem in the coarse, less expensive levels and provides convenient initial guesses at the next finer level. On each level, the corresponding nonlinear system is solved by an iteratively regularized Gauss-Newton method. The multilevel strategy is motivated by convergence results of IRGN. This method is applicable to a wide range of examples as shown in several numerical tests for noiseless and noisy data.
机译:在本文中,我们考虑了紧支撑的线性样条f:R-> C的傅立叶变换(f)在顶盖上的相位恢复问题的数值解,其中垂直线f的垂直线和垂直线(f)的值在有限的多个等距节点上给出了顶盖竖线。复数样条系数的未知相位实现了结构良好的非线性方程组。因此,相位重建会导致非线性逆问题,这可以通过多级策略和迭代的Tikhonov正则化解决。多级策略将解决相位检索问题的主要精力集中在较粗的,较便宜的级别上,并在下一个更好的级别上提供了方便的初始猜测。在每个级别上,通过迭代正则化的Gauss-Newton方法求解相应的非线性系统。多层次策略是由IRGN的收敛结果所驱动。此方法适用于各种示例,如无噪声和高噪声数据的几个数值测试所示。

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