The numerics of phase retrieval

A Fannjiang, T Strohmer - Acta Numerica, 2020 - cambridge.org
Phase retrieval, ie the problem of recovering a function from the squared magnitude of its
Fourier transform, arises in many applications, such as X-ray crystallography, diffraction …

Conditional neural holography: a distance-adaptive CGH generator

Y Asano, K Yamamoto, T Fushimi, Y Ochiai - arXiv preprint arXiv …, 2024 - arxiv.org
A convolutional neural network (CNN) is useful for overcoming the trade-off between
generation speed and accuracy in the process of synthesizing computer-generated …

Data-driven phase retrieval using deep generative models

MO Kaya - 2024 - search.proquest.com
This thesis addresses the nonlinear inverse problem of phase retrieval, which is the process
of recovering a signal from the magnitude of its Fourier transform, a fundamental challenge …