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An Adaptive Prediction-Correction Method for Solving Large-Scale Nonlinear Systems of Monotone Equations with Applications

机译:一种自适应预测方法,用于求解应用的单调方程的大规模非线性系统

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摘要

Combining multivariate spectral gradient method with projection scheme, this paper presents an adaptive prediction-correction method for solving large-scale nonlinear systems of monotone equations. The proposed method possesses some favorable properties: (1) it is progressive step by step, that is, the distance between iterates and the solution set is decreasing monotonically; (2) global convergence result is independent of the merit function and its Lipschitz continuity; (3) it is a derivative-free method and could be applied for solving large-scale nonsmooth equations due to its lower storage requirement. Preliminary numerical results show that the proposed method is very effective. Some practical applications of the proposed method are demonstrated and tested on sparse signal reconstruction, compressed sensing, and image deconvolution problems.
机译:本文组合了多变量光谱梯度法,提出了一种自适应预测校正,用于求解单调方程的大规模非线性系统。所提出的方法具有一些有利的属性:(1)逐步是逐步的,即迭代之间的距离和溶液组之间的距离是单调的距离; (2)全球收敛结果与优点函数及其Lipschitz连续性无关; (3)它是一种无衍生法,可以应用于求解大规模非流动方程,因为其较低的存储要求。初步数值结果表明,该方法非常有效。在稀疏信号重建,压缩感测和图像折耦问题上证明和测试了所提出的方法的一些实际应用。

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