期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：10
页码：139-150
出版社：SERSC
摘要：The sensing matrix has an important influence on the original signal sampling and reconstruction algorithm in the compressed sensing theory. A complete random sensing matrix has the drawbacks of largestorage and high complexity in its implementation. In this paper, we propose an interlaced filling algorithm to construct the sensing matrix, which has a quasi-cyclic structure for efficient hardware implementation. The new sensing matrix has small coherence, which provides assurance for the recovery of sparse signal. Meanwhile, some experimental comparison with the other sensing matrix is accomplished. The simulation results demonstrate that the proposed sensing matrix not only obtains better performance but also owns easy hardware implementation.
