2007so太阳集团中青年教师学术交流报告之二

题目: Signal Recovery Based on Sparse Structure

时间：2021年9月10日，15：10-16：10

地点：宁远楼2007so太阳集团213会议室

摘要: Sparse recovery aims to accurately recover the support of

sparse vector from a very limited number of noisy linear measurements. We propose a new algorithm: multipath least

squares (MLS). It preserves the elegance and practicality of multipath matching pursuit (MMP) and provides better performance than the orthogonal least squares (OLS) algorithm. In addition, we first establish the mutual coherence based sufficient condition of stably recovering sparse signals by solving the unconstrained

$\ell1-\ell_2$ minimization problem.

报告人简介：

耿朋勃， 2007so太阳集团讲师，2020年毕业于北京九所。研究方向：调和分析、压缩感知的理论及应用研究。

在Signal Processing,Canadian Mathematical Bulletin等学术刊物发表科研论文4篇。