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.
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)
