期刊文献+

用于压缩感知的二值化测量矩阵 被引量:9

Binarized Measurement Matrix for Compressive Sensing
原文传递
导出
摘要 压缩感知是近年新兴的一种信号处理理论,在一定条件满足的情况下,压缩感知方法可通过远低于Nyquist频率的降采样数据以高概率近乎完美地重建原始信号。测量矩阵在压缩感知的整个处理过程中起着非常重要的作用。本文从恢复算法入手提出二值化测量矩阵,并通过仿真对其性能加以验证。二值化后测量矩阵不仅在性能上有一定提升,更重要的是可大大降低测量矩阵所需的存储空间以及压缩感知采样、恢复过程的运算量。 Compressive sensing( CS) is a newly developed theory in signal processing. If certain conditions are met, the original signal can be recovered nearly perfectly with a very high probability from the sampling data,of which the sampling rate is much lower than the Nyquist sampling rate. Measurement matrix plays a very important role in the entire procedure of CS. In this paper,the binarized measurement matrix is proposed from the perspective of recovery algorithm,and simulations are carried out to verify the performance. After binarization,the recovery performance of measurement matrices can be improved to a certain extent. And most importantly the storage of the measurement matrices and the computation cost of the sampling and recovery of CS can be greatly reduced.
出处 《微波学报》 CSCD 北大核心 2014年第2期79-83,96,共6页 Journal of Microwaves
基金 国家"973"计划(2010CB731904)
关键词 压缩感知 测量矩阵 贪婪恢复算法 二值化测量矩阵 compressive sensing(CS),measurement matrix,greedy algorithm,binarized measurement matrix
  • 相关文献

同被引文献45

  • 1DAI W;MILENKOVIC O.Subspace pursuit for compressive sensing signal reconstruction,2009(05).
  • 2叶梅,叶虎年,杨新立.Hadamard变换光学编码探测中的定位精度研究[J].华中科技大学学报(自然科学版),2007,35(9):81-83. 被引量:1
  • 3Siwei Yu,A. Shaharyar Khwaja,Jianwei Ma.Compressed sensing of complex-valued data[J]. Signal Processing . 2011 (2)
  • 4Richard Baraniuk,Mark Davenport,Ronald DeVore,Michael Wakin.A Simple Proof of the Restricted Isometry Property for Random Matrices[J]. Constructive Approximation . 2008 (3)
  • 5Wei, S.-J.,Zhang, X.-L.,Shi, J.Linear array SAR imaging via compressed sensing. Progress in Electromagnetics Research . 2011
  • 6Cho Sang-Heum,Lee Sang-Hun,Nam-Gung Chan,Oh Seoung-Jun,Son Joo-Hiuk,Park Hochong,Ahn Chang-Beom.Fast terahertz reflection tomography using block-based compressed sensing. Optics Express . 2011
  • 7Jiao Wu,Fang Liu,L. C. Jiao,Xiaodong Wang.Compressive Sensing SAR Image Reconstruction Based on Bayesian Framework and Evolutionary Computation. IEEE Transactions on Image Processing . 2011
  • 8Ming Sheng Chen,Fa Lin Liu,Hong Mei Du,Xian Liang Wu.Compressive Sensing for Fast Analysis of Wide-Angle Monostatic Scattering Problems. Antennas and Wireless Propagation Letters, IEEE . 2011
  • 9Candès, Emmanuel J.,Romberg, Justin,Tao, Terence.Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on Information Theory . 2006
  • 10Boufounos P T,Baraniuk R G.1-bit compressive sensing. 42nd Annual Conference on Information Sciences and Systems . 2008

引证文献9

二级引证文献33

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部