CBMS Conference: Sparse Approximation and Signal Recovery Algorithms

CBMS 会议：稀疏逼近和信号恢复算法

• 批准号: 1642586
• 负责人: Joseph Lakey
• 金额: $ 3.84万
• 依托单位: New Mexico State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1642586&HistoricalAwards=false
• 关键词: CBMS; Conference; Sparse; Approximation; Signal

This grant provides support for the CBMS Conference on Sparse Approximation and Signal Recovery Algorithms, which will take place at New Mexico State University, Las Cruces on May 22-26, 2017. Professor Anna C. Gilbert of the University of Michigan will provide a lecture series on Sparse Approximation and Signal Recovery Algorithms. The subject matter lies at the interface of applied mathematics, electrical and computer engineering, and information science. The subject is chosen to build and strengthen existing research ties between the host institution and other institutions and technical industries in the Southwest region. A primary goal is to bring a large group of researchers in mathematics and applications to the cutting edge of sparse approximation techniques and applications. Sparse approximation problems arise in a variety of applications concerning digital communications and analysis of large datasets. The lecture series will begin with basic mathematical formulations of sparse approximation and signal recovery problems. It will proceed with a discussion of greedy algorithms and convex methods, such as basis pursuit, sublinear algorithms for streaming and sketching, and Fourier sampling methods. The lectures will conclude outlining specific applications such as GPS synchronization, spectrum sensing, and correlation spectroscopy. The principal lecturer Anna C. Gilbert is the Herman H. Goldstine Collegiate Professor of Mathematics at the University of Michigan. She is the recipient of numerous prestigious awards, including the SIAM Ralph E. Kleinman Prize for outstanding contributions that bridge mathematics and applications. Further details, including plans to fund participant travel and registration information, can be found at: https://www.math.nmsu.edu/activities/cbms2017/cbms2017.html

该补助金为CBMS稀疏近似和信号恢复算法会议提供支持，该会议将于2017年5月22日至26日在拉斯克鲁塞斯的新墨西哥州州立大学举行。 安娜教授C.密歇根大学的吉尔伯特将提供关于稀疏近似和信号恢复算法的系列讲座。该学科是应用数学、电子和计算机工程以及信息科学的交叉学科。选择该主题是为了建立和加强主办机构与西南地区其他机构和技术行业之间的现有研究联系。一个主要的目标是使一大群研究人员在数学和应用的尖端稀疏近似技术和应用。稀疏近似问题出现在各种数字通信和大型数据集分析的应用中。系列讲座将开始与稀疏近似和信号恢复问题的基本数学公式。它将继续讨论贪婪算法和凸方法，如基追踪，流和素描的次线性算法，以及傅立叶采样方法。讲座最后将概述具体的应用，如GPS同步，频谱传感和相关光谱。首席讲师安娜C.吉尔伯特就是那个赫尔曼·H。密歇根大学的Goldstine学院数学教授。她是众多著名奖项的获得者，包括SIAM Ralph E。Kleinman奖是为了表彰在数学和应用之间做出的杰出贡献。更多详情，包括资助与会者旅行的计划和注册信息，可在以下网站上找到：https://www.math.nmsu.edu/activities/cbms2017/cbms2017.html