Research on the construction algorithm of measurement matrix based on mixed chaotic

LI Xuezhen; LING Yongfa

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Research on the construction algorithm of measurement matrix based on mixed chaotic

更新时间：2026-09-04

- Research on the construction algorithm of measurement matrix based on mixed chaotic
- Vol. 38, Issue 9, Pages: 23-30(2021)
- 作者机构：
  
  1. 桂林电子科技大学机构信息与通信学院,广西,桂林,541004
  2. 贺州学院机构人工智能学院,广西,贺州,542899
- 作者简介：
- 基金信息：
- DOI：
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- Published：2021
- 稿件说明：
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李雪珍, 凌永发. 基于混合混沌序列的测量矩阵构造算法研究[J]. 微电子学与计算机, 2021, 38(9): 23-30.

LI Xuezhen, LING Yongfa. Research on the construction algorithm of measurement matrix based on mixed chaotic[J]. 2021, 38(9): 23-30.
李雪珍, 凌永发. 基于混合混沌序列的测量矩阵构造算法研究[J]. 微电子学与计算机, 2021, 38(9): 23-30. DOI：

LI Xuezhen, LING Yongfa. Research on the construction algorithm of measurement matrix based on mixed chaotic[J]. 2021, 38(9): 23-30. DOI：

摘要

为了提高测量矩阵的性能，提出了一种基于异或混合混沌序列的测量矩阵构造算法.基于Chebyshev混沌映射和改进型Logistic混沌映射，提出了一种混合混沌映射的数学模型，采用门槛函数法对实值混沌序列进行二值量化，将实值的混沌序列转化为二进制混沌序列；然后通过异或的方式将两种二进制混沌序列结合起来得到混合混沌序列，最后将该混合混沌序列采用循环移位的方式构造成压缩感知测量矩阵.实验结果表明：该算法构造的测量矩阵的重构成功率得到了提高，当压缩比小于0.4时，PSNR提升了大约12 dB.

Abstract

In order to improve the performance of measurement matrix

an algorithm of measurement matrix construction based on XOR mixed chaotic sequence is proposed. Based on Chebyshev chaotic map and advanced Logistic chaotic mapping

a mathematical model of the mixed chaotic map was proposed. By the method of threshold function

real value quantitative chaotic sequence for binary and real value of chaotic sequence can be converted to binary chaotic sequence.Then the mixed chaotic sequence is obtained by combining the two binary chaotic sequences in the way of XOR. Finally

the mixed chaotic sequence is constructed into the compressed sensing measurement matrix by means of cyclic shift. The experimental results show that the success rate of the reconstruction of the measurement matrix constructed by the algorithm is improved

and the PSNR of the measurement matrix is improved by about 12 dB when the compression ratio is less than 0.4.

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references

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