Construction of compressed sensing matrices based on affine symplectic space over finite fields  

作　　者：Wang Gang Niu Minyao Fu Fangwei 

机构地区：[1]Chern Institute of Mathematics and Lab of Pure Mathematics and Combinatorics,Nankai University [2]College of Science,Civil Aviation University of China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2018年第6期74-80,共7页中国邮电高校学报（英文版）

基　　金：supported by the National Basic Research Program of China(2013CB834204);the National Natural Science Foundation of China(61571243);the Fundamental Research Funds for the Central Universities of China;the Ph.D.Candidate Research Innovation Fund of Nankai University(91822144)

摘　　要：The compressed sensing matrices based on affine symplectic space are constructed. Meanwhile, a comparison is made with the compressed sensing matrices constructed by DeVore based on polynomials over finite fields. Moreover, we merge our binary matrices with other low coherence matrices such as Hadamard matrices and discrete fourier transform(DFT) matrices using the embedding operation. In the numerical simulations, our matrices and modified matrices are superior to Gaussian matrices and DeVore’s matrices in the performance of recovering original signals.The compressed sensing matrices based on affine symplectic space are constructed. Meanwhile, a comparison is made with the compressed sensing matrices constructed by DeVore based on polynomials over finite fields. Moreover, we merge our binary matrices with other low coherence matrices such as Hadamard matrices and discrete fourier transform(DFT) matrices using the embedding operation. In the numerical simulations, our matrices and modified matrices are superior to Gaussian matrices and DeVore's matrices in the performance of recovering original signals.

关 键 词：compressed sensing COHERENCE SPARSITY affine symplectic space finite fields 

分 类 号：TN[电子电信]