国家天元数学中部中心高性能计算系列报告 | 常慧宾 研究员(天津师范大学)

发布时间: 2022-06-30 15:58

报告:Fourier Masked Phase Retrieval:Mask Design, Blind Recovery, and Sparsity Modeling

报告时间:2022-07-01  10:30 - 11:30

报告人:常慧宾 研究员  天津师范大学

腾讯会议ID:914-957-139

报告入口:https://meeting.tencent.com/dm/wr54KHDxftze

Abstract: Phase retrieval plays an important role in vast industrial and scientific applications, which is essentially a non-convex and possible non-smooth optimization problem mathematically. As a special and important case, recovery from Fourier masked measurements is critical for practical imaging including x-ray imaging, material sciences, and optics. In this talk, we mainly concern how to design masks for unique recovery, jointly reconstruct the mask and sample, and design fast convergent splitting algorithm with sparsity modeling.