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发表时间:2017-11-02 阅读次数:246次
报告题目: Join Statistics Seminar of SCMS and SDS: Greedy Methods for Compressed Sensing Reconstruction
报 告 人:Dr. Jian Wang
报告人所在单位:
报告日期:2017-11-02 星期四
报告时间:13:30-14:30
报告地点: School of Data Science
  
报告摘要:

Sparse recovery aims to reconstruct high dimensional sparse signals from their low dimensional linear samples. In recent years, sparse recovery has attracted a lot of interest in electrical engineering, computer science, statistics and applied mathematics. This talk is about a classic greedy algorithm called orthogonal matching pursuit (OMP). For its simplicity, ease of implementation, and promising recovery performance`s\vl VE0`s\vl V in practice. This talk will introduce the theoretical limit of OMP in the noiseless scenario and its performance for approximate sup- port recovery under constant signal-to-noise ratio (SNR). This talk will also introduce the generalized OMP (gOMP) algorithm.

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本年度学院报告总序号:247

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