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结构化压缩感知研究进展

刘芳 武娇 杨淑媛 焦李成

刘芳, 武娇, 杨淑媛, 焦李成. 结构化压缩感知研究进展. 自动化学报, 2013, 39(12): 1980-1995. doi: 10.3724/SP.J.1004.2013.01980
引用本文: 刘芳, 武娇, 杨淑媛, 焦李成. 结构化压缩感知研究进展. 自动化学报, 2013, 39(12): 1980-1995. doi: 10.3724/SP.J.1004.2013.01980
LIU Fang, WU Jiao, YANG Shu-Yuan, JIAO Li-Cheng. Research Advances on Structured Compressive Sensing. ACTA AUTOMATICA SINICA, 2013, 39(12): 1980-1995. doi: 10.3724/SP.J.1004.2013.01980
Citation: LIU Fang, WU Jiao, YANG Shu-Yuan, JIAO Li-Cheng. Research Advances on Structured Compressive Sensing. ACTA AUTOMATICA SINICA, 2013, 39(12): 1980-1995. doi: 10.3724/SP.J.1004.2013.01980

结构化压缩感知研究进展

doi: 10.3724/SP.J.1004.2013.01980
基金项目: 

国家重点基础研究发展计划(973计划)(2013CB329402),国家自然科学基金 (61072106,61072108,61173090,61272023),高等学校学科创新引智计划(111计划)(B07048),教育部长江学者和创新团队发展计划 (IRT1170),国家教育部博士点基金 (20110203110006),智能感知与图像理解教育部重点实验室开放基金 (IPIU012011002)资助

详细信息
    作者简介:

    杨淑媛 西安电子科技大学电子工程学院教授. 2005 年获西安电子科技大学电子工程学院博士学位. 主要研究方向为机器学习,多尺度分析,压缩采样.E-mail:syyang@xidian.edu.cn

Research Advances on Structured Compressive Sensing

Funds: 

Supported by National Basic Research Program of China (973 Program) (2013CB329402), National Natural Science Foundation of China (61072106, 61072108, 61173090, 61272023), Fund for Foreign Scholars in University Research and Teaching Programs (111 Project) (B07048), Program for Cheung Kong Scholars and Innovative Research Team in University (IRT1170), National Research Foundation for the Doctoral Program of Higher Education of China (20110203110006), and the Open Research Fund Program of Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China (IPIU012011002)

  • 摘要: 压缩感知(Compressive sensing,CS)是一种全新的信息采集与处理的理论框架. 借助信号内在的稀疏性或可压缩性,可从小规模的线性、非自适应的测量中通过非线性优化的方法重构信号. 结构化压缩感知是在传统压缩感知基础上形成的新的理论框架,旨在将与数据采集硬件及复杂信号模型相匹配的先验信息引入传统压缩感知,从而实现对更广泛类型的信号准确有效的重建. 本文围绕压缩感知的三个基本问题,从结构化测量方法、结构化稀疏表示和结构化信号重构三个方面对结构化压缩感知的基本模型和关键技术进行详细的阐述,综述了结构化压缩感知的最新的研究成果,指出结构化压缩感知进一步研究的方向.
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  • 收稿日期:  2012-09-10
  • 修回日期:  2013-04-09
  • 刊出日期:  2013-12-20

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