TIAN Shujuan, FAN Xiaoping, LI Zhetao, PAN Tian, CHOI Youngjune, SEKIYA Hiroo. Orthogonal-Gradient Measurement Matrix Construction Algorithm[J]. Chinese Journal of Electronics, 2016, 25(1): 81-87. doi: 10.1049/cje.2016.01.013
Citation: TIAN Shujuan, FAN Xiaoping, LI Zhetao, PAN Tian, CHOI Youngjune, SEKIYA Hiroo. Orthogonal-Gradient Measurement Matrix Construction Algorithm[J]. Chinese Journal of Electronics, 2016, 25(1): 81-87. doi: 10.1049/cje.2016.01.013

Orthogonal-Gradient Measurement Matrix Construction Algorithm

doi: 10.1049/cje.2016.01.013
Funds:  This work is supported by the National Natural Science Foundation of China (No.61379115, No.61110215, No.61311140261, No.61372049), Hunan Provincial National Natural Science Foundation of China (No.2015JJ4047, No.12JJ9021,No.13JJ8006), Hunan Provincial Science and Technology Project (No.2014GK3038), and the Construct Program of the Key Discipline in Hunan Province.
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  • Corresponding author: LI Zhetao (corresponding author) is an associate professor and master supervisor in Xiangtan University. His main research interests include wireless network and compressive sensing. (Email: liztchina@hotmail.com)
  • Received Date: 2014-12-30
  • Rev Recd Date: 2015-09-18
  • Publish Date: 2016-01-10
  • An orthogonal-gradient measurement matrix construction algorithm is proposed for reducing the maximum and average mutual-coherence of sensing matrix. It shrinks Gram matrix based on equiangular tight frame theory. An orthogonal-gradient factor matrix is deduced. It obtains an optimized measurement matrix with the orthogonal-gradient factor matrix. The results of experiments show that the proposed algorithm effectively reduces the maximum and average mutual-coherence of sensing matrix. This leads to a better reconstruction performance for signals with different sparsities compared with Gaussian matrix, Elad's, Xu's, Vahid's and Li's methods.
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