题目：Optimal Order for Phase Retrieval Problem Based on Fourier Measurements
主讲人：栗会平
时间：2024-11-26 14:30
地点：#腾讯会议：829-974-278
举办部门：数学与计算机学院
讲座要点：
The classical phase retrieval problem is to recover original signals from Fourier measurements. However, the analyses of many effective algorithms are based on random Gaussian measurements. This leads to a wide gap between theory and practical applications. In this talk, we mainly focus on the phase retrieval problem under masked Fourier measurements which occurs in many applications such as diffraction imaging. To solve such problem, we intend to discuss two types of models for dealing with different types of noise. Namely, L_2-norm loss function for bounded noise and L_1-norm loss function for outliers. Then we use the gradient-based algorithms (TWF and TAF) and prox-linear algorithm to handle different models, respectively. Further, for such algorithms mentioned above, we have reduced the sampling complexity to the optimal level O(n log n), which implies that we have thoroughly resolved an open question proposed by E. J. Candès et al.
主讲人简介：
自2016-2020年于浙大硕博连读，师从博导：李松教授，硕导：莫群教授。自2020年底至今在杭州师范大学数学学院工作。近5年主持国家自然科学基金1项，参与3项，目前主要研究方向为信号处理及相位恢复，以及相关问题的理论与算法分析。曾以第一作者在Inverse Problems、Advances in Computational Mathematics、Inverse Problems and Imaging等期刊发表论文。