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Deterministic Construction of Compressed Sensing Matrices using BCH Codes

机译:用BCH确定压缩感知矩阵的构造   代码

摘要

In this paper we introduce deterministic $m\times n$ RIP fulfilling $\pm 1$matrices of order $k$ such that $\frac{\log m}{\log k}\approx \frac{\log(\log_2n)}{\log(\log_2 k)}$. The columns of these matrices are binary BCH code vectorsthat their zeros are replaced with -1 (excluding the normalization factor). Thesamples obtained by these matrices can be easily converted to the originalsparse signal; more precisely, for the noiseless samples, the simple MatchingPursuit technique, even with less than the common computational complexity,exactly reconstructs the sparse signal. In addition, using Devore's binarymatrices, we expand the binary scheme to matrices with $\{0,1,-1\}$ elements.
机译:在本文中,我们介绍确定性$ m \次n $ RIP满足$ \ pm 1 $阶$ k $的矩阵,使得$ \ frac {\ log m} {\ log k} \ approx \ frac {\ log(\ log_2n )} {\ log(\ log_2 k)} $。这些矩阵的列是二进制BCH码向量,其零被-1取代(不包括归一化因子)。通过这些矩阵获得的样本可以轻松转换为原始的稀疏信号。更准确地说,对于无噪声样本,即使比通常的计算复杂度低,简单的MatchingPursuit技术也可以精确地重建稀疏信号。另外,使用Devore的二元矩阵,我们将二元方案扩展为具有$ \ {0,1,-1 \} $个元素的矩阵。

著录项

  • 作者

    Amini, Arash; Marvasti, Farokh;

  • 作者单位
  • 年度 2009
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
  • 中图分类

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