Earticle

초록

영어

Compressed sensing is a revolutionary technology in the research eld of signal processing,
which can reconstruct the sparse signal using fewer number of compressive measurements
compared with conventional reconstruction methods. Compressed sensing can also be utilized
to detect the sparse signal. However, the exact reconstruction operation is not necessary
when the system aims to detect such sparse signal. Based on compressed sensing, a new
compressive signal detection scheme using the sparsity order of the sparse signal is proposed
in this paper. Compared with similar detection scheme using the supports of the sparse
signal, the newly proposed scheme requires much fewer number of compressive samples. In
particular, the proposed scheme does not require the support prior-information of the sparse
signal. Simulation results verify the advantages of the proposed scheme and indicate that
the new scheme can achieve better detection performance.

목차

Abstract
 1 Introduction
 2 Related Work
  2.1 Compressed Sensing
  2.2 System Model
  2.3 Support Detection
 3 Sparsity Order Detection
  3.1 Sparsity Order
  3.2 Sparsity Order Detection Algorithm
 4 Simulations
 5 Conclusion
 References

키워드

저자

• Shaohua Qin [ School of Control Science and Engineering, Shandong University, China, College of Physics and Electronics, Shandong Normal University, China ]
• Dongyan Chen [ School of Control Science and Engineering, Shandong University, China ]
• Xu Huang [ School of Control Science and Engineering, Shandong University, China ]
• Leilei Yu [ School of Control Science and Engineering, Shandong University, 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