Improved Measurement Matrix Construction with Pseudo-Random Sequence in Compressed Sensing

Author(s):  
Jiai He ◽  
Tong Wang ◽  
Chanfei Wang ◽  
Yanjiao Chen
2014 ◽  
Vol 644-650 ◽  
pp. 1007-1010
Author(s):  
Hua Xu

Measurement matrix construction is important to compressed sensing. A novel method, MMC-DE (Measurement Matrix Construction based on Differential Evolution), is proposed in this paper. The matrix is based on the quasi-cyclic Low-Density Parity-Check (LDPC) code. This proposed method aims at constructing the quasi-cyclic matrix with the best girth during the optimization procedure. It can consequently result in improving the reconstruction performance of the measurement matrix for compressed sensing. Simulation results demonstrate that the proposed measurement matrix is better than the matrix of Tanner code and array code. It is also easy to implement and hardware friendly.


2013 ◽  
Vol 475-476 ◽  
pp. 451-454
Author(s):  
Xue Ming Zhai ◽  
Xiao Bo You ◽  
Ruo Chen Li ◽  
Yu Jia Zhai ◽  
De Wen Wang

Insulator fault may lead to the accident of power network,thus the on-line monitoring of insulator is very significant. Low rates wireless network is used for data transmission of leakage current. Making data compression and reconstruction of leakage current with the compressed sensing theory can achieve pretty good results. Determination of measurement matrix is the significant step for realizing the compressed sensing theory. This paper compares multiple measurement matrix of their effect via experiments, putting forward to make data compression and reconstruction of leakage current using Toeplitz matrix, circulant matrix and sparse matrix as measurement matrix, of which the reconstitution effect is almost the same as classical measurement matrix and depletes computational complexity and workload.


2022 ◽  
Vol 188 ◽  
pp. 108592
Author(s):  
Ping Wang ◽  
Xuegong Liu ◽  
Xitao Li ◽  
Dawod Al-Qadasi ◽  
Linhong Wang

Optik ◽  
2020 ◽  
Vol 220 ◽  
pp. 164783
Author(s):  
Qi Qin ◽  
Yan Liu ◽  
Zhongwei Tan ◽  
Muguang Wang ◽  
Fengping Yan

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