2017-11-22-温金明学术报告：Integer and Sparse Signal Recovery: Theory and Algorithms

报告题目：Integer and Sparse Signal Recovery: Theory and Algorithms

报告人：温金明

摘要：In many applications, such as wireless communications, signal processing and GPS, we need to recover an integer parameter vector from an integer linear model. While in some other application domains including computer vision and machine learning, one is frequently required to recover a sparse signal from a few measurements. In the first part of this talk, we will first theoretically show that some commonly used lattice reductions, which are preprocess tools for recovering integer vectors, can always improve the success probability of some commonly used suboptimal recovery algorithms, and then show that they can decrease the complexity of the optimal method for detecting integer vectors. In the second part of the talk, we will introduce some algorithms and theory for recovering sparse algorithms from a few measurements.

报告人简介：温金明，2008年6月毕业于吉林化工学院理学院，获理学学士学位；2010年6月毕业于吉林大学数学研究所，获理学硕士学位；2015年6月毕业于加拿大麦吉尔大学数学与统计学院，获哲学博士学位。从2015年3月到2017年8月，温博士先后在法国科学院里昂并行计算实验室以及加拿大阿尔伯塔大学从事博士研究工作。 从2017年9月至今，他在加拿大多伦多大学从事博士后研究工作。他的研究方向主要是整数信号和稀疏信号恢复的算法设计与理论分析。他以第一作者在Applied and Computational Harmonic Analysis，IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing等顶级期刊和会议发表23篇学术论文。目前他担任IEEE Access（SCI检索）期刊的编辑。