Gradient descent in phase retrieval

Q2 Mathematics
Massimo Cicognani, Alberto Bernardini, Alessandro Ilic Mezza, Roberto Leone Cicognani
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引用次数: 0

Abstract

Alternating projections, like Griffin-Lim and Fast Griffin-Lim algorithms, are among the most widely used iterative methods for phase retrieval. In this paper, we build upon the appendix of the original paper by Griffin and Lim and formulate them as gradient descent algorithms. By this approach, we can give convergence guarantees, evaluate the rate of convergence, and introduce a new phase recovery method based on the Nesterov acceleration of the gradient descent.

相位检索中的梯度下降
交替投影,如Griffin-Lim和Fast Griffin-Lim算法,是最广泛使用的相位检索迭代方法之一。在本文中,我们以Griffin和Lim原始论文的附录为基础,将它们表述为梯度下降算法。通过该方法,我们可以给出收敛保证,评估收敛速度,并引入一种新的基于Nesterov加速度的梯度下降相位恢复方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annali dell''Universita di Ferrara
Annali dell''Universita di Ferrara Mathematics-Mathematics (all)
CiteScore
1.70
自引率
0.00%
发文量
71
期刊介绍: Annali dell''Università di Ferrara is a general mathematical journal publishing high quality papers in all aspects of pure and applied mathematics. After a quick preliminary examination, potentially acceptable contributions will be judged by appropriate international referees. Original research papers are preferred, but well-written surveys on important subjects are also welcome.
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