Orthogonal-Gradient Measurement Matrix Construction Algorithm
Tian Shujuan, Fan Xiaoping, Li Zhetao, Pan Tian, Choi Youngjune, and Hiroo Sekiya
Chinese Journal of Electronics, vol.25, no.1, pp.81-87, Jan., 2016. [pdf document]

<Abstract>

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?fs, Xu?fs, Vahid?fs and Li?fs methods.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?fs, Xu?fs, Vahid?fs and Li?fs methods.