Earticle

초록

영어

The sensing matrix has an important influence on the original signal sampling and reconstruction algorithm in the compressed sensing theory. A complete random sensing matrix has the drawbacks of large storage and high complexity in its implementation. In this paper, we propose an interlaced filling algorithm to construct the sensing matrix, which has a quasi-cyclic structure for efficient hardware implementation. The new sensing matrix has small coherence, which provides assurance for the recovery of sparse signal. Meanwhile, some experimental comparison with the other sensing matrix is accomplished. The simulation results demonstrate that the proposed sensing matrix not only obtains better performance but also owns easy hardware implementation.

목차

Abstract
 1. Introduction
 2. The Theory of Compressive Sensing
 3. The Construction of Sensing Matrix via Interlaced Filling Algorithm
  3.1. A Representation of Matrix by a Distance Graph
  3.2. The Construction of Sensing Matrix
  3.2. The Coherence and Spark of Constructed Sensing Matrix
 4. The Results and Analysis of Experiments
 5. Conclusion
 References

키워드

저자

• Yang Nie [ Digital Engineering Center, Communication University of China, Beijing, China / Department of Physics, Jining Normal University, Inner Mongolia, China ]
• Xin-Le Yu [ Digital Engineering Center, Communication University of China, Beijing, China ]
• Zhan-Xin Yang [ Digital Engineering Center, Communication University of China, Beijing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605