JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2017, Vol. 52 ›› Issue (11): 23-28.doi: 10.6040/j.issn.1671-9352.0.2017.093

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gOMP reconstruction algorithm based on generalized Jaccard coefficient for compressed sensing

ZHANG Xiao-dong1, DONG Wei-guang1,2*, TANG Min-an1, GUO Jun-feng3, LIANG Jin-ping4   

  1. 1. School of Electrical Engineering and Automation, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China;
    2. Key Laboratory of Opto-Technology and Intelligent Control Ministry of Education, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China;
    3. School of Mechanical and Electronic Engineering, Lanzhou University of Technology, Lanzhou 730050, Gansu, China;
    4. School of Astronautics, Northwestern Polytechnical University, Xian 710072, Shaanxi, China
  • Received:2017-03-12 Online:2017-11-20 Published:2017-11-17

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Abstract: In order to solve the problem such as low reconstruction performance of the signal, we propose a generalized orthogonal matching pursuit(gOMP)reconstruction algorithm based on generalized Jaccard coefficient. The improved gOMP algorithm replaces matching criterion of inner product by similarity matching criterion of generalized Jaccard coefficient, and selects the most matching atom from projection matrix and residual signal. Experimental results show that the reconstruction success rate of proposed algorithm is much better than other algorithms, such as gOMP, OMP, StOMP and so on.

Key words: compressed sensing, generalized orthogonal matching pursuit, similarity matching criterion, reconstruction algorithm, generalized Jaccard coefficient

CLC Number: 

  • TP391
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