报告题目：Iterative Methods for Compressed Sensing报告人：徐洪坤教授
报告时间: 7月1日上午10：00
报告地点：南山校区1号楼415室 数学系教师休息室
报告人简介：
徐洪坤教授是国际著名的非线性泛函数分析及其应用方面的专家。他的主要研究领域为非线性泛函分析与优化、非线性反问题之迭代方法和金融数学中的定价问题。鉴于徐洪坤教授在科学研究中的成就，他于2004年皇冠hg8868老版本被授予南非数学界最高奖－2004年皇冠hg8868老版本南非数学会杰出研究奖和教育部自然科学二等奖。徐洪坤教授是台湾中山大学西湾讲座教授，南非科学院院士，华东理工大学特聘教授；曾任南非夸祖鲁—那塔尔大学教授，沙特阿拉伯沙乌特国王大学教授。现为《Nonlinear Analysis》等十余种国际数学杂志副主编和编委，担任80余种数学和工程期刊审稿人。发表论文大约170多篇，被引用600多次，单篇论文最高被引用105次。
报告内容简介：
Abstract：Compressed sensing is a novel technique in signal processing for efficiently acquiring and reconstructing signals by exploiting the sparseness or compressibility of a signal. It has been received much attention from both applied mathematicians and engineers of many applied _elds such as communication theory, imaging sciences, optics, radar technology, sensor networks, and tomography. Sparseness of a signal makes possible full recovery of the signal with undersampling. Mathematically, this is a underdetermined linear system and its sparse solutions can be sought by optimization methods.
The purpose of this talk lies in reporting some iterative methods for solving optimization problems arising from compressed sensing. These methods include the iterative reweighted least-squares, the iterative hard/soft thresholing algorithm, and the proximal gradient algorithm.
