caa a22 4500 60620993X CHVBK 20210128101031.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s11220-015-0109-0 doi (NATIONALLICENCE)springer-10.1007/s11220-015-0109-0 Symmetric Toeplitz-Structured Compressed Sensing Matrices [Elektronische Daten] [Tao Huang, Yi-Zheng Fan, Ming Zhu] How to construct a suitable measurement matrix is an important topic in compressed sensing. A significant part of the recent work is that the measurement matrices are not completely random on the entries but exhibit some considerable structures. In this paper, we proved that a symmetric Toeplitz matrix and its variant can be used as measurement matrices and recovery signal with high probability. Compared with random matrices (e.g. Gaussian and Bernoulli matrices) and some structured matrices (e.g. Toeplitz and circulant matrices), we need to generate fewer independent entries to obtain the measurement matrix while the effectiveness of the recovery keeps good. Springer Science+Business Media New York, 2015 Compressed sensing nationallicence Restricted isometry property nationallicence Measurement matrix nationallicence Symmetric Toeplitz-structured matrix nationallicence Huang Tao Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, 230039, Hefei, People's Republic of China aut Fan Yi-Zheng Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, 230039, Hefei, People's Republic of China aut Zhu Ming Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, 230039, Hefei, People's Republic of China aut Sensing and Imaging Springer US; http://www.springer-ny.com 16/1(2015-12-01), 1-9 1557-2064 16:1<1 2015 16 11220 https://doi.org/10.1007/s11220-015-0109-0 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11220-015-0109-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Huang Tao Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, 230039, Hefei, People's Republic of China aut NATIONALLICENCE 700 1- Fan Yi-Zheng Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, 230039, Hefei, People's Republic of China aut NATIONALLICENCE 700 1- Zhu Ming Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, 230039, Hefei, People's Republic of China aut NATIONALLICENCE 773 0- Sensing and Imaging Springer US; http://www.springer-ny.com 16/1(2015-12-01), 1-9 1557-2064 16:1<1 2015 16 11220