Reconstruction of High Dimensional Data via Weighted Norm Minimization Methods
报告题目(Title)：Reconstruction of High Dimensional Data via Weighted Norm Minimization Methods
报告人(Speaker)：谌稳固 （北京应用物理与计算数学研究所）
地点(Place)：后主楼12层1223
时间(Time)：2019年12月27日 14:00-15:00
邀请人(Inviter)：薛庆营
报告摘要
In this talk, we consider the reconstruction conditions for the exact reconstruction of data with structures in the noiseless setting and approximation in the noisy case from incomplete information. The structure includes sparsity, the context when some prior information on the support of the signals is available. Moreover, we consider the optimality or sharpness of these sufficient conditions.
主讲人简介
谌稳固，北京应用物理与计算数学研究所研究员，博士生导师，主要从事调和分析、非线性色散方程、大数据分析的理论及应用研究，在Applied and Computational Harmonic Analysis，Signal Processing, Journal of Computational and Applied Mathematics，IEEE Signal Processing Letter, IEEE Access，Inverse Problems and Imaging，CPDE, JDE, Nonlinear Analysis: Real World Applications等学术刊物发表科研论文50余篇。
