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논문검색

Deterministic Construction of Compressed Sensing Matrix Based on Q-Matrix

초록

영어

Compressed sensing is an innovative technology, which provides a new sampling mode. The key problem in compressed sensing is the construction of sensing matrix, which has an important influence on the signal sampling and reconstruction algorithm. At present, in most cases the sensing matrix is a random structure, and is difficult to realize due to its huge storage in practical applications. In this paper, we introduce a novel deterministic construction of sensing matrix via Q-matrix, which is calculated by solving the N-queens problem. The proposed sensing matrix has good orthogonality and circularity. Using the circularity of Q-matrix, we can construct sensing matrix for compressed sensing. A large number of simulation results show that the proposed sensing matrix in this paper can obtain a better quality of the reconstructed image, and it is easily realized owing to its cyclic characteristic.

목차

Abstract
 1. Introduction
 2. Compressed Sensing
 3. Deterministic Construction of Sensing Matrix Based on Q-Matrix
  3.1. The N-Queens Problem
  3.2. Q-matrix
  3.3. The Construction of Sensing Matrix Based on Q-matrix
  3.4. The Coherence of Sensing Matrix Based on Q-matrix
 4. Comparison of Experimental Results
 5. Conclusion
 References

저자정보

  • 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

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