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基于非凸优化模型的块稀疏信号恢复条件

周珺 黄尉

周珺, 黄尉. 基于非凸优化模型的块稀疏信号恢复条件[J]. 应用数学和力学, 2019, 40(2): 167-180. doi: 10.21656/1000-0887.390154
引用本文: 周珺, 黄尉. 基于非凸优化模型的块稀疏信号恢复条件[J]. 应用数学和力学, 2019, 40(2): 167-180. doi: 10.21656/1000-0887.390154
ZHOU Jun, HUANG Wei. Improved Conditions for Block-Sparse Signal Recovery via the Non-Convex Optimization Model[J]. Applied Mathematics and Mechanics, 2019, 40(2): 167-180. doi: 10.21656/1000-0887.390154
Citation: ZHOU Jun, HUANG Wei. Improved Conditions for Block-Sparse Signal Recovery via the Non-Convex Optimization Model[J]. Applied Mathematics and Mechanics, 2019, 40(2): 167-180. doi: 10.21656/1000-0887.390154

基于非凸优化模型的块稀疏信号恢复条件

doi: 10.21656/1000-0887.390154
基金项目: 国家自然科学基金重大研究计划(91538112); 国家自然科学基金青年科学基金(11201450)
详细信息
    作者简介:

    周珺(1994—),女,硕士生(E-mail: 1812253174@qq.com);黄尉(1977—),男,教授,博士,硕士生导师(通讯作者. E-mail: whuang@hfut.edu.cn).

  • 中图分类号: O174.2

Improved Conditions for Block-Sparse Signal Recovery via the Non-Convex Optimization Model

Funds: The Major Research Plan of the National Natural Science Foundation of China(91538112); The National Science Fund for Young Scholars of China(11201450)
  • 摘要: 压缩感知(compressed sensing,CS)是一种全新的信息采集与处理理论,它表明稀疏信号能够在远低于Shannon-Nyquist采样率的条件下被精确重构.现从压缩感知理论出发,对块稀疏信号重构算法进行研究,通过混合l2/lq(0
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出版历程
  • 收稿日期:  2018-05-25
  • 修回日期:  2018-12-04
  • 刊出日期:  2019-02-01

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