Earticle

초록

영어

Random equivalent sampling (RES) can composite a waveform with high equivalent sampling rate from multiple low speed sampling sequences. In practical application, the performance of RES signal reconstruction would be degraded by the non-uniform distribution of sampling time. Compressed sensing (CS) theory is adopted to reconstruct RES samples, which could mitigate the inherent coherence of sampling time. However, the CS reconstruction algorithm is sensitive to the signal sparsity level that is unknown in the reconstruction stage. In this paper, we propose a redundancy reduction algorithm for CS base RES signal reconstruction that can ensure reconstruction accuracy while reducing the number of random samples. The experimental results are reported to evaluate the performance of the proposed algorithm.

목차

Abstract
 1. Introduction
 2. Random Equivalent Sampling
  2.1. Fundament of Random Equivalent Sampling
  2.2. CS based Signal Reconstruction
 3. Redundancy Reduction Algorithm
 4. OMP Recovery Algorithm
 5. Experiment
 6. Conclusion
 References

키워드

저자

• Jianguo Huang [ School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China ] Correponding Author
• Li Wang [ School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China ]
• Yijiu Zhao [ School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, 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